Conversation intelligence uses your sales data — call transcripts and recordings, CRMs, notes — and applies NLP (Natural Language Processing) to get actionable insights and metrics.
Armed with these insights, you can analyze call recordings to improve your sales pitch, coach your reps in real-time, and win more deals.
Call tracking helps you get end-to-end visibility of all customer-facing conversations. You can use this information to understand your customer’s pain points and personalize your sales and marketing strategy.
Meanwhile, conversation intelligence analyzes all sales data, rather than just calls, to help you explore the following in real-time:
A key differentiation in the call tracking vs. conversation intelligence debate:
Sales quotas should be aggressive, but realistic, and most of your team should be able to attain their quotas. Here’s how you can calculate realistic sales quotas for your sales reps.
Start by establishing a baseline for your team’s performance — the average number of deals closed multiplied by the average contract value.
It’s important to note that the baseline quota will change each quarter because of factors such as reps available, projected growth, average deal size, holidays and time off.
The next step is to understand each rep’s capabilities and past performance, rather than simply considering your organizational goals.
It would help if you looked at the average calls per day, follow-ups, average deal size, leads allocated and more to get a complete picture of the rep’s past performance and assess their capabilities.
Conversation intelligence gets insights on customer behavior, competition, product experience, and more from your sales data. This information helps sales, marketing, and product teams improve their productivity quickly.
Conversation intelligence for sales teams can be used to boost win rates, coach better, and create stellar playbooks. In addition, marketing teams can tweak their campaigns to connect better with the target audience.
Meanwhile, product teams can better understand the voice of the customer to build superior experiences and offer capabilities that customers truly need.
The ultimate goal of conversation intelligence is to extract value from sales data spread across multiple systems in the sales-marketing tech stack and use it to drive growth.
Good, reliable and timely sales data is at the heart of sales enablement, revenue intelligence, sales coaching and building a data-driven sales organization. Conversation intelligence is the key to compiling that data automatically with AI-powered insights.
If you want to extract value from sales data, conversation intelligence is crucial. Here are some of the top benefits:
1. Get complete visibility of the sales pipeline
According to HubSpot, over 50% of salespeople admit they forget to enter lead and customer data into the CRM. Sales reps also spend 79% of their time on manual tasks that can be automated.
Additionally, sales leaders or managers of large sales organizations can’t go through every customer-facing conversation and gauge its efficiency.
Real-time conversation analytics provide a complete picture of the sales process, deal pipeline, rep performance, call insights, and more, with no manual tasks like data entry. So, sales reps and leaders can monitor the health of the sales pipeline at a glance.
2. Shorten sales cycles
Onboarding new reps and transforming them into sales pros is a lengthy process, if you only rely on sales training or handholding for each call.
Conversation intelligence equips reps with game tapes — the best sales pitches of all time. Moreover, it provides real-time insights to deal with competitor mentions, objections, pricing, monologues, and more during the call. So, sales reps can close deals faster without the extensive involvement of their managers.
3. Know the ‘why’ behind lost sales
Spotting red flags on time and fixing them is the key to reducing the number of lost deals and improving customer retention.
Conversation intelligence helps you analyze lost sales and dissect them to know why these prospects didn’t convert.
Moreover, it can also help you spot at-risk prospects and customers by highlighting certain keywords that indicate the issue bothering your prospects or customers right away.
Since the approach is data-driven, your sales team can course-correct whenever needed to effectively hit their targets.
In addition, sales managers and reps can use this data to develop a strategy to understand buyer sentiment, know how to perform better during future calls, reduce churn and increase the likelihood of account conversion.
4. Handle sales objections and competitor mentions
Analyzing the past sales calls is one of the best ways to understand and deal with sales objections, competitor mentions, pricing concerns, and other tricky topics.
With keyword filtering and analysis, conversation intelligence can take you right to the instances where common objections are raised on a sales call. This helps sales leaders develop scripts aimed at using the objections or competitor mentions strategically in their favor.
Armed with such scripts, sales reps can be more confident during calls and increase the likelihood of converting their prospects.
5. Build an effective sales playbook
Conversation intelligence is vital to building a data-driven sales playbook for sales enablement, equipped with the dos and don’ts based on real experiences.
Using such playbooks, you can identify essential sales insights such as customer pain points, the best way to deliver your sales pitch and value propositions, and objection handling scripts and techniques.
6. Optimize sales coaching and training
Listening to the best sales calls and dissecting them is one of the best ways to train sales reps and coach them into becoming sales pros.
For onboarding and training new reps, sales managers can set up a playlist of the best sales pitches. They can also analyze call performance at a glance when the conversation intelligence software offers them crucial call metrics such as talk:listen ratio and call duration, besides summarizing calls automatically.
Since conversation intelligence enables you to analyze hundreds of sales calls and highlight key moments, sales managers spend less time looking for data and more time providing actionable, valuable feedback to improve sales performance.
Implementing conversation intelligence requires finding the right tool that gels well with the rest of your sales-marketing tech stack. That’s where conversation intelligence software can help.
Conversation intelligence platforms use machine learning algorithms to mine meaningful information from sales calls, CRM and marketing automation data, and more. So, sales managers can discover new sales opportunities, unearth reasons for lost sales, analyze their team’s performance at a glance, and mentor their teams better.
Meanwhile, sales reps can get real-time call assistance, call metrics offering a snapshot of their performance, and other essential data to improve productivity and win rates.
Conversation intelligence platforms offer essential features such as:
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The software should offer real-time insights — cue cards with the relevant context or monologue alerts, for instance — during sales calls. This helps reps capitalize on the right moment, engage more, and leave a better impression on the prospect.
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Conversation AI automatically records and transcribes calls. It also summarizes the critical call moments, enabling sales managers to understand:
Besides these, the conversation intelligence software should enable you to skim through transcriptions, speed through calls and select relevant call bits to share with URLs to offer meaningful feedback.
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Using conversation intelligence software, you should be able to track essential keywords during sales calls. An AI-powered tool goes a step further by generating live alerts to capture critical data points in real-time and use them for further analysis, assessment, or course correction.
A solid conversation intelligence software lets you apply advanced filters to calls and transcripts to unearth meaningful patterns and insights. It also helps you monitor crucial call metrics like script compliance, talk to listen ratio, moments of hesitation, buyers’ sentiments, and so much more.
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Auto-tagging can classify calls depending on identifiers such as quotes, appointment set, purchase made, and more. This helps your sales and marketing teams access the right data with the right context in a jiffy and build campaigns that convert better.
Achieving conversation intelligence is all about getting hold of the right data and building a culture of data-driven sales.
The first step is to take stock of all sales data, current sales processes, and your existing tech stack. This helps you map your data sources and types, identify the gaps in your sales processes and pinpoint the toolkit required to operationalize your sales data.
Then, you should look for a conversation intelligence platform that fits your requirements and integrates seamlessly with the rest of your tech stack.
The last step is to encourage a culture of data intelligence by:
Conversation intelligence scours your data — calls, emails, meetings, CRM, notes — to deliver actionable insights.
Wingman’s conversation intelligence software facilitates revenue enablement and quota attainment for your sales team.
Conversation intelligence is the secret to extracting value from mountains of sales data spread across systems. That’s where a conversation intelligence software like Wingman can help.
Wingman does all the heavy lifting to provide actionable insights on everything from deal intelligence to sales enablement.
Wingman integrates the business platforms and information you already use — your CRM, call logging tool and dialer, video conferencing apps, calendar, and communication channels like Slack.
It then automates actionable insights to guide you through customer sentiment, sales coaching, performance reviews, marketing campaigns and deal intelligence with features such as:
Deal central: Have a single platform for everything you need to know about pipeline health.
Interested in learning more?
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