In today’s consumer-led economy, your ability to improve the customer experience directly impacts whether you close the deal or lose it. If sales teams can’t resolve issues or respond to concerns fast enough, buyers won’t stick around.

That’s why conversational intelligence (CI) is such a powerful tool for sales-focused organizations. It gives you a clear view into your customers’ minds, surfacing what they care about, their pain points, and what ultimately drives their decisions. 

With this level of insight, sales teams and contact centers can fine-tune their approach, strengthen messaging, and close more deals with less guesswork. Think of it as a backstage pass into customers’ motivations delivered in real time. 

Below, we break down the top benefits of conversational intelligence and share best practices to maximize its value.

What Is Conversational Intelligence?

Conversational intelligence involves collecting and analyzing sales conversations to uncover actionable insights, improve experiences, and build stronger customer relationships. And while it may sound like a heavy lift, especially with the volume of calls sales teams handle daily, it’s actually the opposite.

Using innovations like artificial intelligence (AI), natural language processing (NLP), and machine learning, conversational intelligence tools break down customer conversations at scale to deliver meaningful findings. This might mean identifying gaps in messaging, highlighting missed opportunities, or revealing exactly where prospects disengage. 

With these insights in hand, your team can focus on high-value tasks, like refining pitches, building relationships, and closing deals.

How Can Conversational Intelligence Benefit Sales Teams?

If you’re like many companies right now, you’re keeping a close eye on spending. It makes sense: Budgets are tighter, and every investment needs to earn its place. However, conversational intelligence may be the missing link between your team and stronger sales performance. 

From speeding up issue resolution to delivering sharper customer insights, conversational intelligence helps teams move faster, sell smarter, and adapt in real time. It’s more than just a CX tool—it’s a competitive edge for businesses that want to rise above the noise and stay there. 

Here’s how it helps sales teams thrive at every stage of the sales cycle:

Speed Up Customer Issue Resolution

Sales reps deal with a steady stream of questions, concerns, and objections before closing deals. Keeping track of them all isn’t easy, unless they’ve got the memory of an elephant. 

That’s where conversational intelligence earns its keep. It monitors sales conversations in real time, identifies common problem areas, and flags patterns before they derail. With these insights, reps can resolve issues faster and keep momentum going. Sometimes, that’s the difference between a sales cycle that takes weeks and one that drags on for months. 

Boost Agent Performance and Job Satisfaction

Trying to close a deal without understanding your customers is like taking a shot in the dark. You might get lucky, but more often than not, you’ll miss the mark. 

Conversational intelligence reduces that risk. It analyzes customer interactions to highlight what drives conversions and where prospects tend to drop off in the sales cycle. These conversation insights can be used to train sales teams and support agents more effectively, boosting their confidence, sharpening their skills, and improving overall performance. 

The ripple effect? Greater job satisfaction and higher retention. And considering that the cost of replacing a team member can be three to four times their salary, that’s a win worth investing in.

Lower Service Costs and Streamline Response Times

Depending on your industry, sales costs can eat up 15–30% of total revenue. But they don’t have to. 

When you invest in solutions that help you shorten the sales cycle, like conversational intelligence, you cut the guesswork and reduce the cost per sale. Instead of chasing dead ends or repeating the same ineffective tactics, reps can focus on what actually moves deals forward. Fewer wasted sales calls. Fewer missed opportunities. Lower service costs. 

CI also helps your team move faster by pinpointing common customer questions and proven resolutions. The result is faster, more consistent reply times that keep customers engaged and momentum high.

Increase Customer Lifetime Value

Top-performing sales teams don’t just aim for one-time conversions—they build relationships that last.

Conversational intelligence helps by providing valuable insights into what inspires trust, loyalty, and long-term engagement. It can spotlight standout messaging, high-performing reps, and service tactics that turn first-time buyers into brand advocates. With these insights, you can strengthen connections and unlock meaningful revenue growth over time.

Think of it as a playbook for improving customer retention, repeat business, and referrals without having to guess what works.

Prove the Value of Customer Service Efforts

It’s not always easy to link customer service to business results, but conversational intelligence makes it possible.

By turning customer interactions into measurable data, CI allows you to track critical metrics like resolution speed, customer satisfaction score (CSAT), and follow-up success. These insights help connect your team’s efforts to real-world outcomes, like increased sales, reduced churn, and higher retention. 

And in today’s “Era of Less,” when decision-makers are tightening budgets, that kind of return on investment (ROI) clarity can make all the difference.

Best Practices for Implementing Conversational Intelligence in Sales Strategies

The best tools only deliver value when they’re implemented intentionally. Here are a few best practices to help you get the most out of your conversational intelligence platform and ensure it’s fully integrated into your sales strategies:

1. Choose the Right Platform

The wrong tool won’t just underdeliver: It might drain resources that are better used elsewhere. That’s why choosing the right conversational intelligence tool is critical.

Start by clarifying your team’s goals. Looking to strengthen sales coaching? Choose a platform that goes beyond summarizing call recordings and includes agent scorecards and coaching workflows. Need real-time insights to improve sales processes on the fly? Prioritize tools with live conversation analysis.

Equally important: integration. Your platform should connect seamlessly with your existing tools, like customer relationship management (CRM) software, to support consistent workflows. It also needs to be intuitive and scalable—something your team can grow with, not just test and abandon after a quarter.

2. Train Your Sales Team

Conversational intelligence is powerful, but only when your team knows how to use it.

Training shouldn’t stop at platform features. Reps need to understand why the tool matters, what kind of insights it delivers, and how to turn those insights into action. For example, if you’re introducing a new insight or behavior to focus on, explain how it connects to outcomes your team cares about, like stronger conversions or a shorter sales cycle.

Take a hands-on approach during sales coaching. Give agents opportunities to explore the new platform, review real call recordings, and practice applying conversational data to actual conversations. The more real it feels, the more likely it’ll stick.

3. Focus on Key Metrics 

Conversational intelligence tools can deliver a lot of data. Without focus, it’s easy to get lost in details that don’t drive outcomes.

Start by identifying the metrics that matter most to your team. These might include talk-to-listen ratios, objection-handling success, competitor mentions, or deal progressions. Once you know what to watch, use those insights to shape sales strategies and boost rep performance. 

For example, if a data trend shows that reps are dominating the conversation, it may be time to coach more active listening. The goal is to connect the data back to what actually moves deals forward.

4. Integrate into the Sales Workflow

Conversational intelligence shouldn’t feel like extra work. If it does, adoption will drop fast.

Make it part of the natural flow by integrating it with your CRM (for easier follow-ups) and collaboration tools (to streamline insight sharing). Automate message and call uploads wherever possible so reps can stay focused on conversations, not admin work.

The most effective teams embed CI into every stage, from prospecting to post-sale check-ins. When it’s baked into every step, it consistently delivers value and supports customer progression through the sales cycle. 

5. Celebrate Wins and Socialize Insights

It’s human nature to fixate on what’s not working. But highlighting what is working builds momentum and motivation.

Celebrate standout moments by recognizing team members who consistently handle calls well. Something as simple as a “Rep of the Week” spotlight for top performers can boost morale, strengthen team culture, and encourage others to level up.

Just as important: socialize your CI insights. Share winning conversations from high-performing reps during team meetings or through collaboration tools, so the whole team can learn from what’s working in real time.

6. Listen to the Voice of the Market

Your customers are already telling you what they need—you just have to listen.

Conversational intelligence tools help you do exactly that by analyzing customer interactions at scale. They reveal emerging needs, market trends, and concerns that are essential to staying competitive. It can also capture customer expectations, making it easier for your team to align messaging with what you can actually deliver and guide future development decisions.

To get even more value, set up keyword alerts for things like feature mentions or pricing concerns. Then review the results with your broader team (sales, management, product development, and marketing teams) to turn raw insights into actionable strategies. 

Key Features of Conversational Intelligence for Sales 

The right conversational intelligence analytics software can transform how your sales team sells, but only if it has the features to back it up. If you’re evaluating tools, prioritize ones that are purpose-built for performance, insight, and scale:

• AI text and call summaries: Automatically condense long conversations into short, digestible snippets, making it easier to review and act on insights quickly.
• Conversational analytics: Analyzes the flow, tone, and context of conversations to uncover customer sentiment, buying signals, and opportunities to improve the experience.
• Text analytics: Makes sense of unstructured data and highlights trends, anomalies, and recurring themes in customer feedback. 
• Transcription capabilities: Converts recordings to text for easier call analysis and coaching 
• Impact prediction: Forecasts how a rep’s actions are likely to influence outcomes, using historical data to support faster, smarter decision-making.
• Agent and coach scorecards: Provides a clear view of team performance, spotlighting strengths and opportunities for improvement. 

Transform Your Sales Outcomes With InMoment’s Conversational Intelligence

Conversational intelligence has shifted from nice-to-have to a competitive necessity. It empowers sales teams to improve performance, boost job satisfaction, and better understand and respond to customers’ needs and expectations. With the right insights, you can reduce friction in the sales process, build stronger relationships, and unlock long-term growth.

InMoment’s customer experience platform brings it all together. Our conversational intelligence tools analyze phone calls, chat logs, email threads, and survey responses—turning complex data into clear, actionable insights. Your team gets a complete view of what’s working, what’s not, and where to focus next to drive real results.

See how InMoment’s conversational intelligence software can help your team close more deals and elevate the customer experience—schedule a demo today.

You can’t fully predict customer behavior from day one. People are unpredictable, and what resonates with one group might fall flat with another. 

That’s where A/B testing shines. It helps you test messaging, support strategies, marketing campaigns, and experience variations to optimize interactions, streamline support processes, and improve the overall user experience. 

But while traditional A/B testing tells you what performs better, conversational intelligence reveals why. It adds context to the data, uncovering customer sentiment, intent, and pain points that quantitative metrics alone can’t explain—fueling more targeted optimization and data-driven decision-making.

Let’s explore how conversational intelligence enhances the A/B testing process and how to implement it effectively.

Why Traditional A/B Testing Falls Short Without Conversational Intelligence

A/B testing (also known as split testing) is essential for customer experience optimization, but on its own, it can only take you so far in aligning CX efforts with broader business goals. Over time, traditional A/B testing tends to hit a wall for a few key reasons:

• It focuses on surface-level metrics like conversion rates, response times, customer satisfaction score (CSAT), and Net Promoter Score (NPS) but it lacks the qualitative context behind them. It doesn’t tell you why a customer felt frustrated, delighted, confused, or compelled to stay.
• It can be misleading when it fails to capture emotional responses. For example, a customer might complete a purchase or subscribe (boosting your conversion metrics), yet still feel dissatisfied with the experience. Traditional A/B testing would mark that as a win, even if that frustration puts long-term retention at risk.

How Conversational Intelligence Enhances A/B Testing

Conversational analytics software brings critical context to A/B testing. It goes beyond numbers to explain why customers behave a certain way, making it a powerful addition to your conversion analytics toolkit. When you understand the reasons behind user choices, you can refine experiences with greater precision.

Let’s break down how conversational intelligence strengthens A/B tests.

Uncovers Customer Pain Points and Friction Areas

If you’re testing different versions of your messaging, support strategy, or landing page, traditional A/B testing tools can tell you which variation performs better than the control group, but not explain the reasons behind it. That’s helpful, but it won’t show you where customers are getting stuck or what’s turning them away.

Conversational intelligence fills in those gaps. Analyzing service chats, voice transcripts, and chatbot interactions reveals the pain points and friction areas in the version that underperforms, giving you clear direction on what needs to be improved. 

Example: An A/B test for a new support chatbot shows that Version A is the clear winner. CI analysis reveals that customers find Version B confusing because it lacks clear instructions and key functionality—insight that wouldn’t show up in standard performance metrics.

Automates Feedback Collection and Analysis

Let’s be honest: manual data collection from live chats, emails, call center logs, surveys, and support tickets is tedious, time-consuming, and nearly impossible to scale. 

CI tools automate this process by using machine learning and natural language processing (NLP) to scan through large volumes of customer communication. They turn unstructured feedback into in-depth, actionable insights, helping you make smarter, faster decisions about what to run tests on next.

Example: CI detects complaints about hard-to-find contact options in one variation, highlighting a usability issue that shapes your next A/B test. 

Identifies Customer Sentiment and Satisfaction Drivers

Metrics like click-through rates (CTRs) can tell you which A/B test version performs better, but they won’t tell you how customers actually feel about the experience. That’s where customer conversations come in.

CI tools use sentiment analysis to evaluate word choice, tone, and emotion across interactions. This helps you identify the experiences that generate positive sentiment and, just as importantly, the ones that don’t. With these insights from real user conversations, you can fine-tune future A/B tests to focus on what truly resonates. 

Example: A brand tests two versions of a customer onboarding flow. CI sentiment analysis reveals that Version A causes frustration due to overly complex steps, even though completion rates are the same. Armed with this insight, the brand simplifies the experience in the next test to boost satisfaction. 

Enhances Personalization and User Engagement

With 81% of consumers preferring brands that deliver personalized experiences, understanding your customers on a deeper level isn’t optional—it’s essential. Conversational intelligence helps you get there.

By analyzing how customers speak and what they care about, CI helps personalize the experience and sharpen your marketing strategy—from content and messaging to segmentation by behavior, preferences, and demographics. For example, you can apply CI insights to location-based campaigns to uncover what’s not working for users in a specific region and tailor the testing process to address that user group’s pain points directly.

These insights improve your next test and enable quick, meaningful adjustments that make customers feel heard and understood. 

Example: One chatbot variation offers proactive solutions based on prior customer pain points, leading to higher engagement and fewer escalations.

Detects Emotional Reactions to Service Changes

Customer behavior isn’t always a reliable indicator of satisfaction. People may use a new feature or follow a script simply because they’re in a hurry or don’t want the hassle of switching providers. Traditional A/B testing might interpret this engagement as a success, even if the experience causes frustration.

CI fills in the emotional gaps. It uncovers patterns of confusion, irritation, or delight that typical metrics miss, helping you avoid rolling out changes that create hidden friction or long-term dissatisfaction.

Example: A new automated refund process is A/B tested. Both Version A and Version B receive similar engagement, but CI finds that Version B generates fewer complaints and more positive sentiment in support interactions.

Refines Customer Messaging and Support Strategies

Conversational intelligence takes the guesswork out of A/B tests by highlighting the exact words, requests, phrases, expressions customers use. 

Instead of testing random messaging variations or support strategies, you can focus on the language and guidance that actually matters, like the phrasing of a call-to-action (CTA), chatbot guidance, or self-service instructions.

Example: CI reveals that customers repeatedly ask for a “talk to an agent” option. That insight leads to a clearer escalation pathway in the winning variation, improving both satisfaction and resolution rates.

Steps to Implement Conversational Intelligence in A/B Testing

Conversational intelligence is the lens that sharpens your A/B testing vision. It provides context (the why behind customer choices) that helps fine-tune tests and accelerate CX improvements. But to unlock its full value, it’s important to implement it thoughtfully and avoid common mistakes, like relying only on quantitative data or overlooking emotional drivers in customer conversations.

Here’s how to get started:

1. Identify Key Conversational Data Sources (Chatbots, Customer Support Logs, Social Media Comments)

Capturing valuable insights starts with assessing a variety of customer touchpoints. The more channels you analyze, the more complete your view will be of customer preferences, concerns, and questions.

Collect conversational data from multiple sources (like social media comments, chatbot logs, support transcripts, call recordings, and feedback forms) to ensure your A/B testing process reflects the full spectrum of the customer experience. 

2. Use AI-Powered Conversational Intelligence Tools to Analyze Themes, Sentiment, and User Intent

Manually reviewing thousands of customer interactions isn’t realistic, and limiting your insights to a small sample size can lead to skewed or incomplete conclusions. That’s where AI-powered tools come in.

Conversational intelligence platforms act as advanced analytics tools, helping you move beyond raw feedback to spot actionable trends. They can detect user sentiment, recurring themes, and user intent in real time. These tools help you uncover patterns, like frustrations around your checkout process, that directly inform A/B test decisions and future CX refinements.

3. Integrate Conversational Insights With A/B Test Results

Once you’ve implemented your AI-powered CI tool, the next step is to combine its insights with your existing A/B test metrics. For example, if traditional A/B testing shows that customers prefer Version B, conversational intelligence can help uncover the why behind that preference, like clearer messaging, better support tone, or fewer points of friction.

Blending these insights moves your A/B testing beyond surface-level performance data, giving you a clearer view of how to optimize the experience based on customer perception, not just user behavior.

4. Iterate and Refine A/B Test Variations Based on These Insights

Conversational intelligence insights are only as valuable as the actions you take on them. Use what you learn to continuously refine your A/B test variations—whether that means updating the messaging, adjusting design elements on a webpage, or simplifying processes. 

For example, if CI data shows that customers describe your pricing page in Version B as “confusing,” revise the structure and run another test. Continue iterating until customer sentiment improves and the data confirms you’ve found a version that truly works.

Gain Deeper Customer Insights With InMoment

A/B testing shows what performs better, but conversational intelligence reveals why. Together, they help your team move beyond surface metrics to uncover what truly drives customer behavior, improves the user experience, and accelerates CX optimization.  

To get the most from your A/B testing process, invest in a CI tool with AI-powered analytics. These tools help you quickly identify patterns, sentiment, and intent across high volumes of customer interactions. 

InMoment turns conversation data into a competitive edge. Our AI-powered customer experience platform analyzes interactions across contact center calls, chats, surveys, and more—highlighting preferences, friction points, and emotional responses. These insights show why one A/B test variation outperforms another so you can iterate faster, improve with confidence, and deliver experiences that truly resonate.

Schedule a demo to see how InMoment’s AI-powered CX platform can help you elevate your A/B testing strategy!

Sales forecasting is essential for anticipating demand, allocating resources, and setting realistic revenue goals. Forecast accuracy is crucial; otherwise, businesses risk overlooking growth opportunities and wasting resources.

However, according to Gartner research, forecasting is one of the top areas where sales operations functions are least effective. Traditional forecasting processes often miss the mark as they don’t account for the latest market changes or shifts in consumer preferences.

Therefore, businesses must look beyond historical sales data and integrate customer experience insights with their forecasting models for accurate results.

The Benefits of an Accurate Sales Forecast

Accurate sales forecasting empowers businesses to make informed decisions that drive customer satisfaction and sales. Here are some key benefits:

• It helps optimize resource allocation. Businesses are more likely to improve inventory management, staff performance, and budget allocation if they set realistic sales targets.
• It improves cash flow management. The ability to forecast revenue streams allows businesses to maintain financial stability.
• It strengthens sales strategies. Sales teams become flexible since they can adjust their outreach efforts based on market trends.
• It boosts investor confidence. Accurate sales forecasts signal strong financial health, which helps secure investor interest and funding.
• It provides a competitive advantage. When businesses can confidently predict sales, they are better equipped to capitalize on shifts in customer preferences and stay one step ahead of the competition.

What Factors Impact Sales Forecasting Accuracy?

Businesses must consider several internal and external factors to achieve accurate sales forecasts. Each factor affects the usefulness of sales predictions, from new releases and legislative changes to outdated tools and incomplete data.

Internal Factors

Internal misalignment is a significant roadblock for accurate sales forecasts. Poor communication, staff changes, and resource constraints contribute to unpredictable revenue growth.

• Poor communication impacts the quality of data businesses feed into their forecasting models. Misaligned marketing, sales, and finance teams cannot effectively share data, resulting in forecasts based on incomplete information.
• Staff changes in your sales and marketing teams impact sales volume and stability. For example, if your best-performing sales managers leave, their accounts will likely experience a temporary decline that conventional models don’t factor into their predictions.
• Resource constraints in technology and the workforce present a significant hurdle for accurate predictions. A lack of investment in predictive analytics tools and experts leads to guesswork rather than data-driven predictions. Therefore, your business will likely struggle to predict revenue growth without the right sales forecasting methods and personnel.

External Factors

Sales forecasts are vulnerable to unpredictable external influences that businesses cannot control. Competitor activity, market trends, and economic downturns all impact consumer demand.

• Market trends dictate consumer preferences, so predicting them is key to accurate sales forecasting. For example, failing to anticipate declining customer demand from a specific region can lead to overestimating future revenue growth.
• Competitor activity affects your market share and sales volume. For example, if your competitor adopts an aggressive pricing strategy, you’re likely to see your sales drop below the expected figure. Therefore, a good practice is to invest in competitor analysis software that leverages AI to keep you in the loop regarding key players in your space.
• Macroeconomic factors such as GDP growth, exchange rates, and retail sales present a significant forecasting challenge. While businesses can’t control economic conditions, they must stay informed to adjust their forecast methods accordingly.

Technological Limitations

Without omnichannel data collection and AI-driven insights, your business will struggle to collect and act on valuable competitor and customer data. You won’t be able to account for key sales growth factors, leading to missed opportunities and inefficient resource allocation. Therefore, AI-enabled sales forecasting software is essential for setting realistic targets.

How CI Transforms Sales Forecasting

Conversation Intelligence (CI) is a data-driven approach to collecting, interpreting, and analyzing interactions between customers and businesses. It captures textual and audio data from multiple channels to provide comprehensive insights into customer behavior. Here are five key ways this effective data collection and analysis helps generate realistic sales forecasts.

Comprehensive Data Analysis Across Channels

CI collects and connects customer experience data from every relevant source to build a comprehensive dataset for analysis. These sources include contact center calls, chat transcripts, surveys, and emails. 

It’s crucial to invest in an omnichannel customer experience platform like InMoment that doesn’t miss out on key insights. Unlike a multichannel platform, an omnichannel tool doesn’t use each channel independently. Instead, it seamlessly integrates data across these channels to provide a unified view of customer interactions.

For example, a user’s online review provides limited information on its own. However, connecting the review to the same user’s call transcript and survey responses uncovers a clearer picture of their unique experience.

Insights and Emerging Trend Detection

Once you have the data in place, you can dig into it to spot trends in customer behavior. CI leverages machine learning to extract these valuable insights. This AI-driven approach helps businesses proactively address pain points, with 70% of consumers believing there is a clear gap between companies that leverage AI to serve them and those that don’t. It also enables sales and marketing alignment by providing both departments with a unified view of market trends.

Sentiment and Behavioral Analysis

Monitoring customer behavior trends is helpful, but it’s also worth understanding the drivers behind these shifts. CI addresses this requirement by using Natural Language Processing (NLP) techniques, such as sentiment analysis, to decode customer emotions, effort, and intent. 

With InMoment’s core NLP engine, you achieve low-latency text extraction and analytics capable of processing over five social media posts per second. This comprehensive analysis helps you anticipate customer needs and adjust your sales forecasts accordingly.

Impact Prediction and Opportunity Prioritization

CI relies on past sales data to predict future buying patterns. It leverages machine learning algorithms to pinpoint the most impactful sales drivers, including customer sentiment, product demand, and competitor activity. With this insight, businesses can prioritize high-impact sales and marketing strategies.

Focused Insights on Individual Speakers

The best CI tools support comprehensive analysis across your organization. For instance, InMoment’s conversation intelligence software lets you drill down into each actor’s input in a customer-agent interaction. 

The agent-specific insights help call center managers to motivate top performers and identify agents who require additional training. Meanwhile, the customer insights highlight intent and sentiment in a conversation to gauge satisfaction levels.

Key Benefits of Using CI for Sales Forecasting

CI helps businesses identify trends and issues early, enabling proactive steps to improve sales performance. Here are six positive results of incorporating this technology for improving forecast accuracy.

Improved Ability to Identify Market Trends and Customer Behaviors

CI tools analyze vast amounts of customer interaction data across channels like social media and phone calls to detect emerging trends and behaviors. This analysis enables sales teams to anticipate shifts in market demand and respond accordingly. For example, if CI highlights a growing expectation for free trials during sales discovery calls, businesses can increase customer satisfaction by re-evaluating their pricing strategy.

Increased Sales Efficiency by Targeting the Right Opportunities

Another key benefit is efficient sales cycles for finding, qualifying, and converting high-quality leads. CI platforms help build automated workflows to save valuable hours that sales reps can invest in winning over qualified prospects.

InMoment’s CI tool, for instance, features intelligent auto-tagging to categorize large volumes of feedback in real time. This automatic categorization routes and organizes interaction data, thus handling routine tasks and freeing up time for agents to build strong customer relationships.

Competitive Advantage in Adapting to Trends Faster

CI gives businesses a real-time pulse on emerging trends, providing a significant edge in a hypercompetitive market. This continuous analysis helps companies to identify changing preferences, new demands, and growing pain points. 

For example, if your SaaS company detects increased mentions of AI-powered automation in customer queries and competitor mentions, you can move ahead of the pack. Integrating AI into your product roadmap and establishing your topical authority through marketing will help you address a growing need. As a result, you will boost customer retention and your market share.

Improved Products, Processes, and Marketing Through Customer Insights

Analytical insights into customer behavior are also useful for improving products, processes, and marketing strategies. CI unveils recurring customer pain points, popular feature requests, and common objections that surface during sales calls. This information empowers businesses to go beyond basic listening by actively incorporating customer feedback into their operations for enhanced satisfaction.

Enhanced Agent Feedback and Training via Communication Patterns

The analysis of agent-customer interactions is valuable for both actors. For instance, CI often works as part of contact center automation to support effective agent training. Managers receive the insight necessary to create targeted coaching programs that address strengths, weaknesses, and communication gaps. This data-driven coaching helps agents communicate effectively, reducing call times and improving customer satisfaction.

Efficient Speaker Data Analysis for Knowledge, Handle Time, and First Call Resolution

An important aspect of agent-specific analysis is evaluating on-call performance, including the agent’s knowledge and speed of issue resolution. CI tracks these conversations to help identify knowledge gaps and communication hurdles. 

For example, analytical insights can indicate if agents tend to hesitate when discussing pricing. Managers can respond with effective scripts and training to improve call center metrics like first call resolution and average handle time. As a result, speaker data analysis helps reduce operational costs while driving conversions.

Steps to Implement CI for Sales Forecasting

1. Choose the Right CI Platform

2. Collaborate with Your CI Provider to Tailor for your Needs 

3. Train Your Sales Team

4. Measure and Optimize

A carefully planned CI strategy can still fail without proper execution. The following steps, from selecting the right tool to training your sales reps, maximize the impact of this analytical approach.

Choose the Right CI Platform

Your CI software should be scalable, easy to use, and customizable. It should also integrate seamlessly with your existing infrastructure. Involve key stakeholders in the decision-making process to evaluate your business strategy and identify the right tool.

InMoment’s conversation analytics platform provides a user-friendly interface for surfacing actionable insights across all communication channels. Its customizable machine learning models allow businesses to fine-tune them with industry-specific jargon and data, ensuring accuracy and relevance. 

The platform’s CX integrations also allow companies to connect data across their tools, from automation to CRM systems. Therefore, instead of rethinking workflows or tech stack, they can immediately incorporate analytics to reduce time to value.

Collaborate with Your CI Provider to Tailor for your Needs

Off-the-shelf solutions rarely deliver optimal results because businesses can’t tailor them to their needs. Therefore, a good practice when investing in a CI tool is to look for professional support from the vendor.

For example, partnering with InMoment enables you to access both the technology and relevant expertise. Our professional team of data scientists, product specialists, and CI consultants work directly with clients to tweak models, automate workflows, and connect insights to existing forecasting tools. Instead of a generic solution, organizations receive a customized product supported by expert consultation.

Train Your Sales Team

Training your sales reps to use CI tools empowers them to personalize their approach to potential customers. Prospects who feel heard and valued are more likely to convert and trust the brand. Therefore, it’s no surprise that personalization leaders are 71% more likely to report improved customer loyalty.

Measure and Optimize

You should continuously monitor your CI-enabled forecasting performance to ensure accurate long-term results. Start by measuring and visualizing key performance indicators (KPIs) like forecast accuracy and conversion rates.

A real-time analytics dashboard, such as the one offered by InMoment, supports this step by providing instant visibility into these metrics. This regular visualization ensures that CI efforts align with shifting market conditions and evolving customer needs.

Enhance Your Sales Forecasting Accuracy with InMoment

Accurate sales forecasting helps improve resource allocation and financial stability for increased investor confidence. However, factors like outdated technology and the broader macroeconomic environment make it challenging to predict future sales.

Your ability to forecast sales depends strongly on how well you can anticipate fluctuations in customer behavior. With InMoment’s conversational analytics software, you gain rich insights into customer sentiment and agent performance. These insights enable you to proactively identify pain points and opportunities for improvement before your competitors. 

Schedule a demo today to see how you can increase sales performance with higher conversion rates!

Businesses deliver seamless customer experiences when their sales and marketing teams are on the same page. Research from Gartner suggests that sales teams prioritizing alignment with marketing are nearly three times more likely to exceed new customer acquisition targets. 

However, as a result of data silos and a lack of common goals, companies often struggle to achieve this alignment. Conversational intelligence offers a data-driven solution by enabling both teams to access shared insights into customer expectations.

Understanding Conversational Intelligence (CI)

Conversation intelligence (CI) is an AI-driven approach to analyzing and optimizing customer conversations. It leverages natural language processing (NLP) to extract actionable insights from speech and text data. These insights guide strategy for delivering positive experiences that boost customer retention and satisfaction.

CI extracts information across multiple channels, including phone calls, emails, social media feedback, and chat transcripts. It analyzes sentiment, intent, and tone to highlight recurring issues and areas for improvement in customer relationships. For example, CI can identify the most frequent category of complaints during support calls to flag common pain points.

These analytical capabilities also support marketing and sales efforts to convert prospects. Sales teams use CI to understand communication strategies tailored to their audience. Meanwhile, marketing teams leverage the insights to fine-tune messaging and campaigns.

The Consequences of Misaligned Sales and Marketing Teams

Misalignment between sales and marketing teams creates a negative ripple effect. It results in inefficient operations and poor customer experiences. For example, this disconnect causes marketing teams to generate leads that sales teams can’t convert. Prospects receive inconsistent messaging that doesn’t work for them, resulting in lost opportunities to add to the bottom line.

How Can You Tell if Your Marketing and Sales Teams are Misaligned?

Siloed operations make it difficult to identify misalignment between marketing and sales teams. When both departments have separate goals, fragmented data, and no cross-team communication, you’ll struggle to see how they affect each other. Key misalignment indicators to look for include:

• Inconsistent Messaging: Customers experience conflicting messaging because of misalignment. For example, your marketing team will push your product’s standout feature, while your sales representatives will focus on discounts. It’s unclear whether you’re competing on value or price. This inconsistency breeds confusion and mistrust, affecting your brand reputation management efforts.
• Lack of Shared Goals: A clear sign of misalignment is when sales and marketing departments have separate objectives. Consider a case in which marketing prioritizes lead volume while the sales team cares more about the closing revenue. Without a single common metric, productive collaboration between both teams is difficult.
• Poor Lead Quality: Do your sales and marketing teams agree on what constitutes a qualified lead? If they don’t see eye-to-eye on lead scoring, your business will struggle to target the most valuable prospects. As a result, your customer acquisition efforts will be ineffective.
• Communication Gaps: A lack of cross-team communication results in missed opportunities. If your marketing executives launch a social media campaign without informing sales, there will be confusion when leads start engaging. Responding to customers within 24-48 hours boosts retention by 8.5%, so any delay from salespeople will be costly for your business.
• Conflicting Strategies: Misaligned strategies also indicate a disconnect between sales and marketing. Internal friction occurs when, for instance, sales pushes certain products to meet quotas while marketing campaigns promote entirely different services. This approach creates a jarring experience for customers, making it difficult for them to trust you.

How CI Facilitates Sales and Marketing Alignment

According to an Accenture study, businesses using AI to align sales and marketing achieve a 34% boost in revenue growth. Here are four key ways CI connects both teams.

Provides Real-Time Insights Across Teams

Immediate awareness of customer sentiment gives businesses a competitive edge by enabling quick and effective action. Tools like InMoment’s customer intelligence platform pull experience data from multiple channels and perform real-time analysis for informed decision-making.

Marketing teams use these insights to hit the right notes with their target audience. Sales teams use the same information for closing deals and acquiring ideal customers. Since both departments have the same, up-to-date data, they can work with the right insights to streamline the overall customer experience.

Improves Customer Understanding

CI allows businesses to explore customer goals and pain points in detail. The comprehensive insights empower marketing and sales teams to better address customer needs. Each team relies on key data points like entity, intent, and sentiment to guide their strategies.

If CI identifies a recurring “negative” sentiment associated with the “product delivery” entity, the marketing team can react by highlighting faster delivery options in its campaigns. The sales team can take proactive steps to assure potential customers of timely delivery during outreach.

The shared understanding of a major customer pain point allows both teams to work on consistent messaging and engagement. Customers feel heard and valued, increasing their brand loyalty over time.

You can simplify this process by leveraging an industry-standard text analytics tool. InMoment’s conversation analytics software lets you extract user intent and emotions from conversational data. This quick insight into experiences helps you improve your services and customer relationships.

Unifies Brand Messaging and Strategy

Consistent messaging is crucial for brand perception and trust. Your marketing team should produce content that resonates with your audience while addressing common concerns to support sales processes. Both teams should receive training on using the same content strategy to complete their tasks.

CI enables this alignment by looking at conversations across sales and marketing channels. It highlights differences in how both teams communicate product features, for instance. 

Businesses can address these discrepancies by rallying their teams around a shared North Star metric. This approach provides a common goal for each department, making it easier to track progress and drive improvements.

For example, if Net Promoter Score (NPS) is the North Star metric, both teams understand that the goal is to enhance brand advocacy. Marketing highlights the glowing reviews shared by promoters. Meanwhile, sales can tailor its pitches to include elements that worked well for existing promoters. The result is a smooth and trustworthy customer journey that boosts satisfaction.

Tracks and Measures Team Effectiveness

The data-driven insights from CI also help track team performance. Conversation analysis indicates customer satisfaction levels when interacting with marketing or sales teams. It measures metrics like response times and sentiment for this purpose.

If CI suggests that sales reps struggle with quick issue resolution, managers can correct this by providing training or effective scripts. As a result, businesses understand areas for improvement in their outreach efforts. These insights help guide teams, address performance bottlenecks, and meet customer expectations.

Steps to Implement Conversational Intelligence for Alignment

1. Identify the Right CI Tools for Your Organization’s Needs

2. Partner with Your CI Provider for Proper Customization

3. Integrate CI With Your Existing Sales and Marketing Systems

4. Train Both Teams on How to Use the Platform Effectively

5. Set Measurable Goals and Track Performance Over Time

The role of CI in facilitating marketing and sales alignment is clear. It organizes valuable information like customer intent and sentiment in one place to encourage collaborative outreach. The same insights also help managers track and improve team members’ performance. Now that you understand the value of CI, here are five key steps for implementing it in your business.

1. Identify the Right CI Tools for Your Organization’s Needs

Investing in a comprehensive CI tool is the first step toward alignment between your teams. Besides offering a rich set of features, including omnichannel data collection, text analytics, and reporting, the tool should be customizable.

Start by asking yourself what you want to achieve with conversational intelligence. What is the exact metric you want to improve? Are you focusing on customer churn or lead generation? A common understanding of business goals results in customer-centric marketing content that drives sales enablement.

Evaluate and select your CI tool based on the features that are most relevant to your goals. For example, if you want to improve call center performance, you should leverage real-time call transcription from tools like InMoment’s conversational intelligence.

Involve your sales and marketing executives in the decision-making process. Their input will help you identify the tool that best aligns with their respective goals and needs. This step also allows both stakeholders to enhance alignment between their teams.

2. Partner with Your CI Provider for Proper Customization

Off-the-shelf solutions won’t be able to provide the rich insights you need to bridge the gap between sales and marketing. As a result, you must partner with a competent CI provider to ensure the tool fits your unique requirements.

A reliable CI provider works with you to understand your customer profiles, expectations, and team performance. For example, InMoment’s professional CI experts will help ensure your tool reflects your metric of choice in its data collection and analysis.

Another key benefit of working with a CI provider is readily available support. Your CI tool should evolve and adapt to any new challenges you face as a business. This process requires regular updates and hands-on assistance from an expert. Therefore, working with the right provider helps you maximize customer experience ROI while aligning your teams.

3. Integrate CI With Your Existing Sales and Marketing Systems

Seamless integration is a non-negotiable for your CI tool of choice. You shouldn’t have to rethink your workflows or adjust existing systems to make way for conversational analytics. The goal is to provide actionable insights to teams without creating friction.

For example, integrating CI with your CRM allows sales and marketing teams to create strong buyer personas. It supports personalization by highlighting the unique needs of each individual. Similarly, connecting CI with marketing automation tools helps segment customers for targeted outreach.

Additionally, these integrations foster collaboration as they enable the smooth flow of data across systems. Your teams are more likely to use shared insights when there are no information silos. InMoment’s robust CX integrations empower businesses to connect insights with every existing system for smoother experience management.

4. Train Both Teams on How to Use the Platform Effectively

Even the best CI tool for your business will be ineffective if your teams don’t understand it. Proper training is necessary for sales and marketing teams to leverage CI for their daily tasks. They should know how to use features like sentiment analysis to generate high-quality leads or retain customers.

Sales reps could receive training on using CI insights to personalize their sales calls. Meanwhile, marketing teams will benefit from learning trend analysis and campaign optimization. Dedicated training programs and guides will help both teams unlock the full potential of CI.

5. Set Measurable Goals and Track Performance Over Time

A successful CI initiative needs to be results-oriented. Defining clear key performance indicators (KPIs) helps you set measurable goals and motivate teams to work toward them. Common KPIs include conversion rates, churn rates, and customer service metrics like NPS.

Regularly monitoring progress toward your goals helps you identify weaknesses and performance issues. It also enables you to highlight quick wins to motivate similar customer-centric efforts from your teams. As a result, you ensure your CI tool drives meaningful improvement in alignment and outcomes.

Achieve Better Sales and Marketing Alignment with InMoment

Sales and marketing alignment is key to business growth. Shared goals, consistent messaging, and common KPIs allow both teams to generate and convert high-quality leads. On the other hand, a disconnect between both teams results in a lack of brand awareness and trust.

InMoment’s conversation intelligence software helps you close the feedback loop with customers by supporting alignment. It leverages omnichannel data collection and text analytics to provide a comprehensive view of the customer experience in one place. The real-time insights enable a collaborative effort that improves engagement and drives revenue. If you’re looking for a reliable CI provider, schedule a demo today!

The path to real improvement starts with understanding.

Effective communication is the foundation of strong teams, enabling them to collaborate, solve problems, and build better relationships with customers and stakeholders. Nowhere is this more critical than in call centers and customer experience teams, where every interaction shapes customer satisfaction, brand perception, and business outcomes.

Conversational Intelligence (CI) is transforming how teams communicate and grow, particularly in environments where clear, real-time interactions are essential—such as call centers. By analyzing conversation patterns, CI helps businesses understand customer needs more deeply, improve team communication, and identify opportunities for training and development. 

As a result, teams can build stronger relationships, improve collaboration, and continuously refine their approach to service and engagement.

What Does “Conversational Intelligence” Mean?

Conversational intelligence is the technological ability to understand, analyze, and extract meaning and insights from human dialog (and any other conversational text). 

It uses natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) to interpret the sense, tone, content, and even outcome of a conversation. Then CI tools catalog and correlate those observations at scale, revealing patterns in conversational data that businesses can use to improve their operations, performance, and customer satisfaction. 

Benefits of Conversational Intelligence for Team Development

Businesses use conversational intelligence for a variety of purposes. It shows up often in marketing and the sales process (such as with location-based campaigns) and retail (in the form of customer feedback)—but it’s also a great tool for developing contact center teams. 

Here’s how:

1. Better Coaching and Learning Opportunities

CI gives managers and leaders a clearer sense of how well their CX or contact center teams are performing, even identifying specific topics and responses that frequently lead to bad results. 

For example, CI software might identify an unusual number of repeat callers with a similar issue, all of whom got the incorrect answer on call #1. This is a problem every manager wants to solve, but this type of problem could go unnoticed for a long time if you’re using manual methods. 

By identifying learning opportunities and coaching needs early, CI software empowers leaders like you to provide more effective coaching, facilitate knowledge sharing, and promote continuous learning within teams.

2. More Effective Meetings

Conversational intelligence tools are also at the heart of the latest generation of smart meeting tools. We’ve had automatic transcription of what was said in a video meeting for some time now, but CI takes that transcription data and makes it even more useful in several ways. 

CI tools can intelligently summarize meetings (think smart meeting minutes, but more granular if you need more detail), create action items, advise on next steps, and perform other similar smart tasks. Some CI tools can also automatically translate meeting transcripts into other languages.

Together these capabilities enhance the value and effectiveness of meetings, helping to make sure all team members are aligned on action items and next steps.

3. Better Feedback

When feedback is subjective, left up to the interpretation of individual managers, team members may disagree, resist, or even understand the opposite of what the manager was trying to communicate! 

CI helps managers and teams deliver and receive feedback that’s not just opinion—it’s backed up with unbiased evidence that connects behaviors and responses to outcomes.

With CI, feedback isn’t just one person’s point of view anymore. It’s grounded in cold, hard facts. Communication based on facts is clearer, more actionable, and growth-oriented (because it constantly points to outcomes). It helps to grow self-awareness with less defensiveness, reframing issues as growth opportunities requiring follow-up rather than as personal attacks.

4. Greater Productivity and Employee Engagement

CI isn’t just about fixing problems—it also helps businesses lean into what they’re already doing well. 

Organizations can use conversational analytics to identify what kinds of conversational approaches are working well and quickly. Then leadership can communicate those successful, productive tactics to entire teams. 

As others adopt high-performing approaches and leave behind middling and low-performing ones, productivity ticks upward. What’s more, employees grow more involved because success breeds stronger engagement.

5. Better Conflict Resolution

Conversational intelligence tools also help teams navigate conflict more smoothly. Spotting and addressing problems earlier can tamp down the tension that would otherwise build up. 

The neutral, unbiased nature of data helps to lower the temperature, too. Using data to show the connection between behaviors and outcomes keeps things constructive and respectful so they don’t feel quite so personal.

6. Faster Onboarding

When new employees join the team, CI makes it possible to access past customer conversations and see key information in real time. Team members can understand company expectations and culture faster and more fully, and they can also quickly absorb effective ways to interact with customers.

7. Stronger Leadership 

Last, CI can make senior leadership more effective in their work. Leaders can more effectively communicate vision and inspire trust when they have an accurate understanding of workplace performance. Leading by example with CI can help transform company culture into one that prioritizes collaboration, motivation, and shared success.

How To Implement Conversational Intelligence Effectively in Your Team

CI adoption starts with software, but doing it right takes more than just purchasing and setting up software. Follow these steps to start gleaning intelligent insights the right way.

Analyze Features and Choose the Right Software

Start by inventorying your needs. What specifically does conversational intelligence software need to accomplish for your business? List these out and start comparing your needs against feature sets from leading CX and CI tools.

Key features to look for:

• Real-time transcription
• Sentiment analysis
• Reporting capabilities
• Translation functionality

If you’re new to CI or moving on from an older solution, don’t limit yourself during this phase. New features and capabilities may meet needs or solve problems that you don’t yet know are fixable.

Ensure Integration With Your Tools

By the time an organization is ready for an enterprise-grade Integrated CX suite, the business already has a complex tech stack in place. A good solution can replace some of the hardware and software you’re already using to run your business, but you’ll still rely on other tools from other providers for some business functions. 

Select CI tools that integrate seamlessly with the other tools in your tech stack (like collaboration platforms, CRM systems, and communication software) or that have webhooks or API access so you can build your own integrations. By integrating your CI solution with the rest of your tech stack, you’ll avoid workflow disruptions and duplicate data entry.

Customize for Your Team’s Needs

Every business (and even teams within a business) has its own set of goals, unique outcomes they want to achieve through analytics. With many tools the out-of-the-box settings and reports cover the basics for most customers, but you can unlock much richer and more detailed insights by customizing your CI settings to align with specific departmental or organizational goals.

Train and Onboard Team Members

CI tools can deliver powerful insights, but they can also be daunting—and maybe even frightening to contact center agents who worry about performance oversight or “big brother” listening to their work.

Training is key here. When team members understand the power and value that CI tools offer—including the power to perform better as a call center agent—fear melts away and enthusiasm grows in its place. 

And don’t forget an additional layer of practical training or onboarding for the team members and leaders who use your CI suite in a more hands-on way. 

Leverage Insights for Actionable Improvements

CI insights are all about improving. Just about any conversational form of data can be studied, and teams can refine and improve their processes based on what they find.

• Refine communication strategies: Repeat successful tactics and eliminate unsuccessful ones.
• Improve coaching: Make it outcome-focused and data-backed rather than personal and opinion-based.
• Enhance collaboration: Identify communication gaps or points of conflict in internal comms.

By acting on trends and feedback you identify using your CI tool, you can lead your team and organization to steady, ongoing growth and improvement.

Empower Your Team’s Growth With InMoment’s Conversational Intelligence

Conversational intelligence is a truly transformational technology that helps organizations gain a deeper understanding of what’s happening in customer interactions. It’s a powerful tool for unlocking the full potential of your workforce, helping reps refocus on tactics that work.

InMoment is an industry leader in all things customer experience (CX), including conversational intelligence. InMoment helps contact centers understand conversational unstructured data at scale, identifying both effective behaviors and business problems to be solved. 

Start unlocking your conversational data today: Start your InMoment demo now.

Marketing your B2B product without first defining your ideal customer profile (ICP) is like shooting in the dark—you may have all the tools you need to hit your target, but that won’t help much when you have no idea where it is. 

An ICP is a detailed description of the best-fit customer from your target audience. It defines attributes like industry, company, and pain points, making it easier to determine which businesses in your target market would make the best customers. However, creating an accurate ICP is no easy feat, especially if you rely on old-school methods or broad assumptions. 

For a reliable profile, you need modern solutions that go beyond standard firmographics. Enter conversational intelligence (CI)—AI-driven technology that analyzes customer interactions.

Let’s look at how CI can help you refine your ICP. 

What Role Does Conversational Intelligence Play in Refining an ICP?

Conversational intelligence involves using machine learning (ML), artificial intelligence (AI), and natural language processing (NLP) to analyze human conversations. 

It pulls data from touchpoints like social media, chatbots, emails, customer feedback, customer relationship management (CRM) tools, and interactions with customer support, marketing, and sales teams, providing insights into customer intent, sentiment, pain points, and patterns.

Through these insights, you can create highly accurate customer profiles and focus your resources and marketing efforts on the right leads. This is more important than ever since marketing budgets have been on a decline since 2022—you want to make the most of what you have. 

Key Insights from Conversational Intelligence to Refine an ICP

Conversational analytics provide “cheat codes” for building an accurate ICP by unlocking insights beyond obvious firmographics like your customers’ industries. They uncover sentiment, engagement, buying intent, and competitor mentions, giving you a well-rounded view of which target customers are likely to convert. 

1. Identifying Pain Points and Buying Intent

Conversational intelligence uncovers recurring challenges in customer conversations, which can help you determine what your target market struggles with most. It can look for phrases that highlight an unmet need, like “we’re frustrated with” or “we can’t figure out how to.” 

This technology also picks up subtle buying intent signals in text or audio conversations. For example, it can point to highly engaged customers—those actively asking questions about your product in conversations—to help you create an ICP that includes their attributes. 

2. Analyzing Sentiment and Engagement Patterns

Conversational intelligence provides conversation breakdowns that can help you segment customers based on how they feel about your brand—positive, neutral, or negative. 

It highlights customers who use positive language when interacting with your brand, like “This may be just what we need,” helping you focus on the most engaged prospects when creating your ICP. 

3. Extracting Key Demographic and Firmographic Data

CI uses real-world conversation data to spotlight high-converting market segments. If startups use the most positive language and tone, it can point you toward this group, allowing you to refine your ICP to include their specific industry, company age, and company size data. 

CI can also highlight demographic info disclosed in conversations, such as team size, the job titles of key decision-makers, and customer locations. This can help you work on your buyer persona and allow for well-informed location-based campaigns. 

4. Tracking Competitor Mentions and Market Positioning

Conversational intelligence goes beyond basic firmographic data to analyze how potential customers compare your business to competitor brands. 

It tracks competitor mentions in conversations, highlighting which brands potential customers talk about the most, as well as the specific features or offerings they value or, conversely, don’t like. This helps you determine how you stack up against the competition and uncovers who your perfect customers are. 

For example, if companies looking for a particular SaaS solution frequently mention a competitor because it provides specific integrations that your solution doesn’t, you can refine your ICP to focus on businesses that don’t need those integrations. 

5. Optimizing Lead Scoring and Qualification

CI uses qualitative insights from conversations to help teams refine ICP criteria and prioritize high-value leads. It detects signals that point to high interest levels and urgency, such as questions about pricing or phrases like “We need to go to market in the next X months,” pointing to the customer segments that should be on your high-priority list. 

CI also refines lead scoring and qualification by tracking potential customers’ levels of engagement. It highlights those who engage frequently with your team, which can help you refine your ICP to focus on ready-to-buy target accounts. 

6. Uncovering Emerging Trends and Evolving Needs

Customer needs and preferences aren’t static—your ICP shouldn’t be either. 

CI can help you create a dynamic customer profile by detecting shifts in customer behavior, expectations, and industry trends. For example, based on customers’ conversations with your sales team, it can offer insight into new pain points you can solve, helping you expand your current profile. 

How to Leverage Conversational Intelligence to Refine Your ICP

Now that you know the value of CI in profile refinement, how do you leverage it to refine your ICP and fuel your marketing strategies? We’ll show you with this step-by-step guide.

Step 1: Choose a CI Tool and Collect Conversational Data from Various Sources

Your choice of CI tool will impact the value of your data and the accuracy of your ICP. So don’t just pick the first tool you come across. Take time to assess each option, prioritizing features like:

• Transcription capabilities to convert audio recordings to text for seamless AI analytics.
• Conversation summaries to glean key takeaways from potential customers’ interactions with your brand, saving your sales and marketing teams time
• Advanced text analytics to find common themes, pain points, and patterns to streamline the development process
• Real-time insights from analyzing conversations as they occur, ensuring your teams always have access to the latest information

Once you find a tool that ticks all your boxes, collect conversational data from multiple touchpoints, including chatbots, messaging tools, customer interviews, sales calls, and surveys. This gives you a comprehensive understanding of customer needs and behaviors, which can help you develop a basic ICP. 

Step 2: Analyze Conversations for Patterns, Keywords, and Sentiment

Once you’ve collected data and formed a basic ICP, use your CI tool to further analyze conversations for recurring patterns, sentiment, trends, and frequently mentioned keywords. This can reveal customer interests, concerns, and intent, helping you refine your ICP based on what potential customers are actually looking for. 

Step 3: Identify Key Themes to Distinguish High-Value Customers

Narrow your ICP further by leaning on your CI tool to identify characteristics that define the most engaged and profitable customers. Look for commonalities (such as common pain points, product preferences, and buying motivations) in conversations, and then segment customers based on your findings. This differentiates high-intent customers from the rest, making it easier to identify their attributes. 

Step 4: Refine ICP Criteria Using Conversational Insights 

Once you’ve segmented high-value targets from the broader market, look for common characteristics to understand what makes them your best customers. Are they in the same industry? Do they have similar needs? Do they share the same customer base? Do they have a comparable decision-making process? 

If you find common ground, feed the characteristics into your ICP to get a refined demographic, firmographic, and behavioral view of your ideal customer. 

Step 5: Continuously Update ICP with Ongoing CI Insights

You probably don’t have the same needs you did a couple of years ago, and your customers are the same—their needs and expectations will evolve with time. 

Prepare your business for these changes by regularly using conversational intelligence data to understand shifting market trends, customer expectations, and business growth strategies. Then revisit and refine your ICP based on the findings to make sure your marketing campaigns and sales strategies stay relevant. 

Transform Customer Data into Meaningful Insights with InMoment

If you’re targeting businesses that fit your current ICP—but your conversion metrics say otherwise—maybe it’s time to reevaluate who your perfect customer actually is. This time, invite conversational intelligence software to the party. It can help fine-tune your ICP by pointing to high-intent customers based on conversations with your brand. 

InMoment simplifies ICP development by pulling data from every customer touchpoint and uncovering common themes and patterns. 

Our platform goes beyond analyzing conversations to provide a fully integrated customer experience (CX) system that can pull signals from every medium, including CRM tools, to refine your ICP—so you can sell to those who are ready to buy. 

Schedule a demo with InMoment today to learn how our platform can help you create a well-defined ICP that boosts your conversion rates!

Want to improve your account health? Keeping customers happy and engaged is an excellent first step. 

But, if we’re being honest, keeping track of customer relationships with your brand—especially when you have thousands of interactions—isn’t exactly a walk in the park. Some issues may inadvertently slip through the cracks, causing customers to look elsewhere. 

That’s where conversational intelligence (CI) becomes so valuable. It leverages artificial intelligence (AI) to analyze customer conversations, giving you real-time insights into customer sentiment and satisfaction with your brand. 

Great businesses aren’t built on sales alone—they’re built on relationships. Spotting pain points helps you connect, solve problems, and earn trust. If that sounds like a win-win scenario, let’s look at how CI enhances account health efforts.

What Is Conversational Intelligence (CI)?

Conversational intelligence involves analyzing customer interactions with your business to assess engagement, intent, and sentiment. CI leverages technologies like machine learning (ML) and natural language processing (NLP) to assess customers’ language patterns, tones, and response dynamics, eliminating the need to manually sift through thousands of calls, chats, and emails. 

With research showing that a great customer experience (CX) can improve profit margins by 1% to 2%—a considerable amount for large businesses—you need every tool in your toolbox to better understand customers and their needs. 

That’s why it’s important to invest in the right conversational analytics software, one with powerful features that fuel a variety of use cases, such as:

• Automated summaries: Leverages conversational AI technology to highlight key takeaways from customer interactions—so you don’t have to do it manually 
• Transcription capabilities: Converts calls and other audio recordings into text for seamless AI-powered analysis
• Text analytics: Assesses unstructured conversational data and picks up on patterns to highlight common pain points and opportunities 
• Scoring capabilities: Analyzes customer support performance, highlighting strengths and areas for improvement 
• Omnichannel data integration: Monitors customer interactions across every touchpoint (social media, chatbots, messages, and phone calls) for a comprehensive view of customer engagement 

The Connection Between CI and Account Health

CI can significantly impact account health efforts for CX teams by offering valuable insights on how to improve interactions. Here’s a deeper look at how the two relate.

Capturing Customer Sentiment and Satisfaction Trends

CI assesses customer conversations across different mediums, analyzing everything from language to tone in order to detect when customers are happy, frustrated, or dissatisfied—even before their sentiment appears in survey results and support tickets. 

If your CX team notices sentiment and satisfaction are starting to dip, they can proactively engage at-risk customers before minor issues escalate and affect account health. 

Identifying Customer Pain Points and Opportunities for Expansion

CI picks up on commonalities, gathering data that can help you identify concerns, frustrations, and customer intent. 

Are a large swath of customers experiencing a common issue with your product or brand? What would they like you to do better? What do they say drives them toward completing purchases? 

These are all questions CI can answer, helping account managers determine what consumers value most. Identifying—and subsequently addressing—these pain points and opportunities can lead to higher engagement and satisfaction. 

Measuring Engagement Levels to Assess Account Health

While traditional static metrics like service renewals and the number of support requests submitted can offer some insight into account health, they may not provide the full picture. 

For example, service renewals may not always indicate customer happiness, as some customers may be renewing their subscriptions while actively looking for something better. (Hey, we’ve all done this at some point.)

CI goes the extra mile, tracking more reliable factors like response times, interaction frequency, and conversational sentiment. This allows customer success teams to segment accounts by engagement risk, promoting proactive intervention where warranted. 

If a once-active customer starts taking longer to engage with your team, or a once-positive customer begins to express frustration, you can categorize them as high-risk and amp up your engagement efforts to retain interest.  

Key Ways Conversational Intelligence Improves Account Health

It’s not feasible or practical for businesses to invest in every solution on the market, so if you’re wondering whether or not a conversation intelligence platform is worthwhile—we get it. If you still have hesitations about CI’s value, let’s dig deeper into the benefits as they relate to account health.

Enhancing Account Monitoring with Real-Time Analytics

With CI, gone are the days of relying on lagging indicators for decision-making. You can say goodbye to relying on periodic surveys, renewal rates, or gut feelings that never seem to improve customer retention. 

CI continually analyzes customer interactions with your brand across channels to assess sentiment and engagement, providing accurate, actionable insights into your account health. 

Detecting Early Signs of Churn and Dissatisfaction

While customer acquisition is an important investment, customer retention should be a priority. The cost of retaining existing customers is lower than that of acquiring new ones, and it’s also quicker to sell to existing customers.

CI helps nurture relationships with current customers by identifying and highlighting signals of frustration, such as drops in engagement and negative sentiment trends. This way, you can step in with proactive interventions to minimize churn risks and nip dissatisfaction in the bud. 

Automating and Refining Account Health Scoring Models

CI eliminates the need for manual account health tracking by dynamically updating scores based on real-time customer conversations. 

This promotes contact center optimization by easing the burden on your team and providing an evolving and more accurate picture of customer satisfaction. And a dynamic view of customer engagement and satisfaction helps your team prioritize high-risk accounts before it’s too late. 

Reducing Subjective Bias in Account Assessments

Human-based assessments are subjective. Where you see a happy and engaged customer, someone else may see a customer who’s about to jump ship. Unfortunately, relying on gut feelings and inconsistent account reviews could make it challenging to follow up with the right customers on time. 

CI eliminates bias by relying on actual data rather than personal opinions. This can make all the difference when trying to boost customer retention. 

InMoment’s Smart Summaries solution, for example, analyzes conversations and provides data-driven, objective insights into account health. Using our AI-powered technology, contact centers can reduce average handle time (AHT) by 33% by eliminating time-consuming administrative tasks that human agents would typically do. 

Improving Customer Engagement and Personalization

The value of personalization is undeniable. Companies that offer personalized experiences are 71% more likely to register improved customer loyalty, and CI can help your success team personalize experiences by identifying customers’ preferences. 

It looks at changes in customer sentiment under different circumstances, highlighting what your audience values the most. This helps you make well-informed personalization decisions, potentially improving customer relationships by meeting customer needs as they emerge. 

Strengthen Your Account Health Strategy with Conversational Intelligence from InMoment

As customer needs evolve and competition grows, it’s become increasingly important for brands to monitor their account health. CI helps by analyzing interactions across all business channels and providing real-time insights into customers’ sentiment and engagement. 

CI takes the guesswork out of account health management and helps customer success teams be more proactive, reducing churn and improving the customer experience. 

With InMoment’s conversation analytics software, you get a holistic view of customer interactions across all touchpoints. Our conversation intelligence tools not only help you improve customer experiences by showing you what matters most, but also promote superior customer service by providing insights into agent performance for continual improvements. 

Get started with InMoment today to improve your account health with actionable, data-driven insights!

Competition for customers’ attention is fiercer than ever. A wrong move on your part—be it failing to solve customers’ issues or offering subpar support—could see them looking elsewhere, affecting your retention numbers. 

To reduce churn, you need to elevate the customer experience (CX). And we know just the solution to help you: conversational Intelligence (CI). 

CI leverages artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to analyze customers’ interactions with your brand. It provides real-time insights on everything from their pain points to their purchasing triggers, helping you improve experiences and increase sales. 

What Are Conversational Intelligence Insights?

Conversational intelligence insights are findings derived from assessing customer conversations with or about your brand. 

Conversational analytics software monitors interactions across various touchpoints and channels, including phone call recordings, chatbot transcripts, emails, social media platforms, and business messaging apps, providing a comprehensive view of how customers communicate and what they say about you. 

These insights can help you understand customer intent, sentiment, and engagement patterns, improving decision-making, brand-customer communication, and overall customer experiences. 

With 37% of consumers leaving brands solely because of poor experiences, the value of these insights can’t be ignored. Think of them as the secret sauce for building customer loyalty. 

The Key Insights Gained from Conversational Intelligence

Conversational intelligence is the gift that keeps on giving. It provides a wide range of insights—customer sentiment, pain points, common concerns, market trends, and even agent performance. So you never have to guess what customers want, what drives them to action, or how well your teams meet their needs. 

Customer Sentiment and Emotional Tone

With conversational intelligence, you can identify customers who are about to jump ship and focus on retention efforts. 

The technology analyzes conversation tones, word choices, and contexts, highlighting the telltale signs of unhappy, dissatisfied, and disengaged customers early on. Based on these findings, you can segment at-risk customers and take proactive steps to minimize the risk of attrition. 

Customer Pain Points and Needs

Customers often voice their unmet needs, frustrations, and recurring challenges with customer support and sales teams. CI software detects these concerns in real time, giving you the info you need to refine your brand’s offerings and messaging. 

It can show your product development team which features to focus on when creating or updating your offerings, as well as help marketing and sales reps craft messaging that speaks to customers’ frustrations to boost conversion rates. 

Buying Intent and Decision Triggers

Conversational intelligence picks up on both apparent and subtle buying signals by analyzing every aspect of your team’s interactions with potential customers. 

It can pinpoint direct signals, like customers asking when they can get started with your solution, and the not-so-direct ones, like pricing questions. This can help you qualify leads more effectively, allowing you to focus on high-intent potential customers. 

CI technology can also highlight the factors influencing purchase decisions by assessing the kinds of questions customers ask before committing. This can facilitate well-informed development decisions and show you what to highlight in marketing campaigns. 

Customer Preferences and Behavioral Patterns

Communication intelligence reveals customers’ preferred communication styles and channels by assessing how they engage with your brand and their most used mediums. This helps you tailor future communications to align with their preferences. 

The technology also breaks down customers’ product or service preferences, purchasing behaviors, and decision-making processes, which can facilitate better personalization. For example, it can identify customers who frequently reach out to your sales team to better understand products before committing, so you can be proactive in future interactions. 

Objections and Barriers to Conversion

It can be difficult to pinpoint what makes customers hesitate or say no to your offerings, especially if you have many teams working in silos. CI software provides insights by integrating data from sales conversations and inquiries and looking for common concerns among customers who say no. 

These insights can help marketing and sales leaders refine their messaging and pitches for better deal closure rates in future interactions. For example, if your tool reports that customers say no because they’re unfamiliar with your brand, teams can incorporate social proof elements, like customer testimonials and case studies, into future pitches to put potential customers’ minds at ease. 

Emerging Market Trends and Popular Topics

Conversation intelligence software analyzes large data sets, looking for frequently mentioned keywords and phrases. These terms can provide insight into evolving customer needs and industry trends, allowing you to adjust your strategy accordingly. 

If customers ask about sustainability, for example, you can start to budget for eco-friendly initiatives or highlight them in your interactions if you already have some running. Staying ahead of shifting customer needs and expectations helps you stay competitive. 

Competitor Mentions and Market Perception

Conversational intelligence analyzes competitor mentions in interactions, showing you who your biggest competitors are and how customers compare your offerings. This information can help you identify areas where competitors are outperforming you and uncover differentiation opportunities. 

In other words, if customers mention your brand and competitor brands in price comparison contexts, you’ll know to focus on your affordability (if you’re cheaper) or your product’s value (if you’re more expensive) in future conversations. 

Customer Journey Insights and Engagement Patterns

Conversational intelligence tracks customer interactions across different touchpoints, from the point of first contact to post-purchase. By doing so, it can help you identify when customers are the most engaged and where in the sales funnel they drop off—so you know what to improve to boost engagement and conversions. 

It can also highlight customers’ questions or concerns at every stage of their purchase journeys, helping you create the right content for each one. 

Sales and Upsell Opportunities

CI tools detect signals for cross-selling and upselling by analyzing conversations for high-interest phrases and concerns. For instance, if you’re a SaaS brand with tiered plans, it can look for questions about accessing more advanced features or increasing the number of platform users and recommend upselling opportunities. 

These insights can help you capitalize on selling opportunities and maximize your revenue potential. If you offer bundled products, they can also help you better package your offerings to meet customers’ needs. 

Agent Performance and Training Needs

Conversational intelligence doesn’t just monitor the customer’s end. It also evaluates how customer-facing teams handle interactions, pinpointing both high-performing agents and areas that need improvement. 

These insights can inform agent appreciation initiatives and show you what to focus on in training to improve customer satisfaction and sentiment. 

Compliance and Risk Management

CI assesses conversation content and shared information against regulatory requirements, flagging compliance violations that can cause legal risks. This allows you to take appropriate steps to minimize your risk exposure, like engaging legal professionals early. 

The AI-driven technology also analyzes interactions against internal company guidelines and highlights violations, letting you know when policy refreshers or updates are needed. 

Predictive Analytics and Future Behavior Trends

CI can also help you prepare for future challenges or opportunities by predicting customers’ actions based on historical conversation data. 

Say your data shows that customers frequently talk about competitors before they abandon ship. It can look for this red flag in current interactions, letting you know when there’s a high churn risk so you can take proactive retention strategies. 

Similarly, if it determines that potential customers start engaging more frequently just before they’re about to convert, it can look for this signal in current conversations, helping you prepare for increased product or service demand. 

How Different Teams Can Use CI Insights to Their Advantage

Conversational intelligence insights take the guesswork out of many teams’ interactions with customers, empowering them with the information they need to promote positive outcomes. Here’s a quick look at the teams that benefit most and how they can leverage these insights effectively.

Customer Support and Success Teams

CI insights help customer support and success teams protect account health by identifying frustrated and dissatisfied customers. They can then prioritize them for immediate follow-ups and support, potentially reducing churn. 

These insights also highlight recurring concerns, trends, and team performance, which can inform response quality improvement and skill development efforts. 

Example: Contact center agents in the telecom industry use CI to identify customers at risk of churning based on sentiment and engagement patterns, passing them over to retention to proactively address their issues and find a resolution.

Marketing Teams

With most companies cutting marketing budgets first in periods of market uncertainty, marketing teams can’t afford to make unfounded guesses when running campaigns. 

CI insights promote well-informed marketing campaigns by helping teams refine their ideal customer profiles (ICP). They highlight both demographic and firmographic data, as well as areas like pain points and decision triggers—all vital for ICP development. Well-defined ICPs minimize the risk of wasting resources on target markets that are unlikely to convert. 

Further, these insights also reveal customer communication preferences and motivations, which can help teams refine messaging and campaign strategies to resonate better with their target audiences. They also pinpoint high-intent customers and help teams identify them within each geographic area, allowing for well-informed location-based campaigns. 

Example: A B2B marketing team’s CI software detects that customers frequently ask about product integration capabilities. To encourage conversions, the team highlights its solution’s capabilities and mentions the kinds of tools it integrates with in marketing campaigns. 

Sales Teams

The days of pitching to every potential customer and hoping they’ll convert are over—thanks to CI technology. It differentiates hot and cold leads by looking for buying signals like “we’re in the market for something like X,” allowing sales teams to prioritize high-intent segments. 

CI insights also highlight customer pain points and the reasons for hesitation or objections in the sales process, helping teams develop more effective pitches and overall sales strategies. 

Example: A health and wellness sales team uses CI to analyze its interactions with customers and finds that they hesitate to book services because they aren’t sure what’s included. Based on this insight, the team revises its sales pitch to clearly lay out what’s offered in each package and what customers can expect if they sign up.

Customer Insights Teams

Manually combing through mountains of data to understand customer behavior, needs, and preferences can feel like punishment, even for the hardest-working employees. Plus, the process takes a lot of time, which doesn’t cut it in the world of constantly evolving customer needs. 

Luckily, customer insights teams can always use CI. It analyzes large datasets to identify themes, patterns, pain points, and trends that could improve customer understanding. 

Take Discover, one of InMoment’s latest products. It analyzes billions of data points to identify CX insights and sends you notifications in real time, keeping you informed on dynamic customer needs and industry trends. 

Example: Thanks to CI, a customer insights team in the automotive industry determines that sustainability is becoming a growing concern for current customers. Therefore, it recommends that the brand consider adding new models and trim packages to its limited line of electric vehicles. 

Product Teams

CI insights help product teams prioritize feature developments based on direct customer feedback and real-world demand, aligning products with user needs. 

These insights also highlight usability issues that impact the customer experience and product gaps (based on comparisons with competitors), helping product teams focus on developments that positively impact customer retention and brand positioning. 

Example: A software development product team finds that customers frequently struggle to navigate their solution’s interface. To reduce the risk of churn, it prioritizes improving its product’s ease of use over adding new features. 

Ecommerce

CI helps ecommerce teams improve customer service and personalize shopping experiences by analyzing customer interactions related to product inquiries, shipping concerns, and purchase behavior. By addressing deficiencies in these areas, teams can improve conversion rates and minimize cart abandonment. 

Example: CI insights help an ecommerce brand segment customers by the products they show the most interest in, facilitating personalized messaging and offers. 

How To Implement Conversational Intelligence for Actionable Insights

Implementing conversational intelligence into customer interactions is relatively straightforward. Use this step-by-step guide to start leveraging CI for actionable insights in your business.

Step 1: Choose the Right CI Tool

The first step is to choose a reliable conversation intelligence tool that aligns with your needs. Your top priority should be finding one that goes beyond transcribing interactions, providing actionable insights into things like customer engagement levels and pain points. 

That said, transcription capabilities are still pretty great, as they convert audio recordings to text for easier analysis. Other factors to consider include:

• Sentiment analysis: Your tool should be able to gauge whether customers’ feelings toward your brand are positive, neutral, or negative based on their tone and word choice. 
• Summarization: This feature eliminates the need to sift through heaps of customer conversations to gather hidden gems.
• Agent performance metrics: Scorecards can help you identify both high-performing agents and areas for improvement. 
• Categorization capabilities: The ability to classify customer conversations by sentiment, buying intent, or specific keywords can streamline analyses. 

Beyond these factors, you also need to assess a conversation intelligence platform’s ease of use, scalability, security, and integration capabilities before committing to make sure it’s the right fit. 

Step 2: Integrate CI with your Existing CRM, Marketing, and Analytics Platforms

After finding the right tool, integrate it with your current customer interaction systems, including: 

• Customer relationship management (CRM) tools like Salesforce and HubSpot
• Data management solutions like Zapier and Oracle
• Communication platforms like Slack and Gmail
• Review platforms like Outreach and Google Reviews
• Analytics platforms like Google Analytics 

Integrating CI with existing systems promotes a smooth flow of conversation data, making it easier for teams to track insights across customer interactions and marketing campaigns. 

Step 3: Define the Metrics and KPIs your Team Will Track With CI Insights

While less overwhelming than actual conversation data, CI insights can seem like a lot if you don’t know what to focus on. So set clear objectives and define key metrics and KPIs upfront. 

Depending on your objectives, you might track metrics like call resolution rates, engagement scores, lead conversion rates, and customer sentiment scores. If your main reason for investing in CI software is to improve agent performance, for example, call resolution rate would be an excellent metric to monitor. 

Step 4: Use CI Data to Iterate and Refine Strategies Continuously

The final step is to use your CI insights to refine communication tactics, customer support processes, and decision-making across sales, marketing, and product development teams. Focus on the most pertinent or pressing action items first to get a lot of value upfront, then you can start tackling the smaller or less impactful items on your list. 

However, this shouldn’t be a one-time process. Continually leverage CI data to identify patterns, trends, and shifts in customer needs over time, and adjust your approaches to optimize business strategies as markets change. 

Unlock Powerful Conversational Insights With InMoment 

Conversational intelligence unlocks a world of valuable data across many business departments—sales, marketing, customer support, product development, ecommerce, and customer insights. 

Whether you want to help your sales team elevate their pitches, get your development team to work on what customers actually want, or reduce cart abandonment rates by catering to customers’ unique needs, this technology has you covered. 

With InMoment’s conversational intelligence technology, you’ll get insights into everything from customer sentiment to industry trends, facilitating smarter decision-making. Our integrated CX platform monitors and analyzes customer interactions across every medium, ensuring you never miss a beat. 

Learn how InMoment’s CI and analytics technology and centralized CX platform can fuel data-driven improvements throughout your business!