Turning Customer Data Into Actionable Commercial Insights

Converting Customer Engagement Data Into Seller Insights That Inform Decisions, Actions, And Conversations At The “Moments That Matter”

Digitally enabled customers are putting a premium on speed, agility, and personalized customer experience across sales, marketing, and customer success channels.

This is increasing the pressure on sellers to deliver a superior and differentiated customer experience in the fraction of time they engage directly with business-to-business customers. The speed at which customer information must be commercialized and shared across the organization has accelerated to the point where revenue teams and the executives that direct them need selling insights in real-time to compete.

This has growth leaders looking for better ways to use advanced analytics to turn the customer data in their CRM, sales enablement, and digital marketing systems into actionable commercial insights that inform decisions, actions, and conversations at the “moments that matter” in the human selling process.

There is more data around the revenue stream available than ever, but without the right analytics and ability to get the selling insights quickly to front line sellers at the pace of business, it’s all just noise,” says Jeff McKittrick, the Vice President of Sales Execution at Walk Me. “Operations teams need to mine that stream of customer engagement data to uncover the right signals of buyer sentiment, intent, and objections to help expensive sales, customer success, and sales engineering resources perform at their best in live selling conversations.”

Howard Brown, the CEO of ringDNA – who has helped hundreds of organizations leverage insights to grow – emphasizes the importance of turning big data into prescriptive advice and one-to-one coaching to guide and coach revenue teams. “The revenue team doesn’t want big data – they want guidance, recommendations, and prioritization on what to do next,” says Brown. “They need to know what actions will drive value and generate the highest return on their time and attention. We need to use data to focus on revenue teams, not overwhelm them. To transform noise into sales guidance.”

This places a premium on systems, processes, and operations that unify, deploy, and monetize data from many customer engagement systems to enable:

>> Proactive selling guidance delivered in real-time;

>> One-to-one coaching at scale;

>> Better visibility into opportunity potential, account health, and readiness to buy;

>> Closed-loop measurements of seller performance, training effectiveness, and buyer responsiveness.

That is also a big reason why over 90% of growth leaders are consolidating the operations that support sales, marketing, and success according to the Revenue Operations in the 21st Century report. They’ve realized they must take a more coordinated approach to manage valuable customer engagement data from their sales conversations, marketing systems, and customer service interactions and make it available to their revenue teams faster. No longer can they afford to manage customer data in six or more operational and technology silos.

There are several practical ways your organization can start to turn big customer engagement data sets into commercial insights that ignite growth. They include:

1. Integrating data from many customer engagement systems to support seller coaching and guidance – The modern selling engine relies on data sourced from many channels, systems, and touchpoints to support selling decisions, priorities, and presentations. Most organizations are sitting on top of large amounts of customer engagement data in a variety of revenue enablement systems – including CRM, exchange (email and calendar), content management, marketing automation, websites, social media, and customer engagement management systems. And that’s not counting one of the biggest sources of customer intelligence – data from recorded phone calls and Zoom meetings.

Organizations that are able to capture and unify customer data and convert it into commercial insights that enable, optimize, and automate cross-functional sales, marketing, and service workflows will have a competitive advantage over those that don’t. For example, Fortive, a conglomerate of industrial businesses, is integrating customer engagement, sales activity, product usage, and telemetry data to support coaching and guidance of revenue teams. “Advanced analytics is a force multiplier that we are putting to work, “ according to Kirsten Paust, VP of Fortive Business Systems. “More and more of our core commercialization processes are being supported by AI, insights, and technology that enables our teams to get to insight and action faster.

Conversational AI solutions like ringDNA capture, transcribe, and integrate customer engagement data from live sales calls and AI-assisted service agents so it can be used to inform sales coaching, prioritization, and action recommendations. “I think any customer data that exists in a silo can only be justified if you’re trying to solve for a very specific problem,” says Howard Brown, who is a co-author of the Revenue Operations report. “But if you are trying to solve a revenue problem and you’re trying to align your marketing, your sales, your support, and your success team to deliver the best possible experience for your buyer, as well as your seller – then don’t they deserve to have a full picture of the information that led to that phone call? Don’t they deserve to know that this particular customer may have three support tickets and issues with your company? Doesn’t your manager deserve to know what reps are really great at and what value they can drive in their conversations and where they need training? That is how you deliver more revenue, more sustainable growth, and a happier customer base.”

2. Automatically augmenting CRM customer profiles with customer engagement and behavior data in real-time – Most (61%) high-performing marketers are developing a single view of the customer to direct targeting and inform customer engagement programs across a variety of touchpoints according to an analysis by Forbes. These common customer and account profiles fuel an array of event-triggered Account-Based Marketing, sales engagement, digital marketing, and media communications across sales, marketing, services touchpoints. As the “clock speed” of modern selling increases to keep pace with customers’ expectations, these triggers and alerts are happening faster and faster. In many cases in real-time.

To create these profiles, sales enablement teams are employing systems that are able to unify data from many touchpoints, channels, and media interactions into a system of record that stores a common customer profile rather than keep data in independent engagement, enablement, training, and marketing systems.

To ensure data integrity and process consistency, the best of these solutions are able to automatically and immediately augment CRM systems by syncing customer engagement and seller activity data without data entry by reps. As more and more business processes rely on the signals from this profile data, systems that update profiles in periodic batches of even ten minutes can create interval problems in a mature revenue enablement model.

For example, rDNA integrates directly with Salesforce.com to automatically log customer interaction data to enrich CRM files and read and write all data fields within CRM to get a 360-degree view of the customer and improve compliance. “Many sales engagement and conversational intelligence tools use single streams of digital engagement and conversation data to help sales reps with sequences, priorities, and outreach,” continues Howard Brown. “The real value is created by combining conversation data with other engagement data like marketing automation data, external intent data, and opportunity data in CRM to help optimize or prescribe who sellers should be contacting, what actions they should be taking to deliver the best results, and what skills they need to be developing.”

3. Providing front-line sellers with prescriptive guidance in real-time – Sales reps that use AI in selling are almost 5 times (4.9 times) more productive, according to a Salesforce.com survey of 4,900 reps. But for most organizations, the potential of analytics remains underleveraged in front-line selling. Half of the sales reps cannot get access to the data they need. Only a third are using analytics to prioritize and qualify leads. “To make the greatest use of the scarce time we must equip sellers with better information about where the buyer is positioned in the buying cycle and meet them there with the information, content, and plays the buyer needs much faster,” reports, according to Corey Torrence, Managing Director of Blue Ridge Partners, and a co-author of the Revenue Operations in a 21st Century Commercial Model Report. General (Ret) Stanley McChrystal emphasizes the critical importance of speeding up communications in the face of rapidly changing market and customer buying behavior. He advises sales leaders to dramatically increase the cadence of communications from weekly to daily updates to real-time (if possible) to ensure critical decision-making, coaching, and prioritization information cascades down quickly to sellers at the edge of the organizations who must make fast decisions and engage customers with the right messages, solutions, and the right time.

4. Make 1:1 coaching at scale part of an integrated learning and development process – Historically, sales managers have been limited by their span of control and free time for sales call monitoring or “ride-along.”  So they are only able to monitor sales calls and actively coach a limited number of reps. The ability to record sales conversations and compare them to selling outcomes and best practices by integrating with CRM, training, and enablement systems can create a real-time, closed-loop information flow. This gives a sales manager the ability to actively manage and coach many more reps and be there at critical points in the conversations such as common objections, competitive mentions, or signals of attrition. It also lets them understand what training has been adopted, and whether it is successful at changing customer behavior. Continuous, real-time and 1:1 coaching allows sales managers to actively manage and coach many more reps and accelerates how quickly new reps ramp to full productivity.

5. Create measures that close the loop between seller performance, training effectivenessand customer outcomes– Sales leaders are starting to use advanced analytics to derive new measures that more accurately quantify the collective engagement, energy, and customer experience their teams are creating within accounts. They are drawing upon sales analytics solutions to track the behaviors and activities that define team success but ladder up to innovative data-driven customer engagement measures and incentives tied to opportunity potential, account health, and seller performance on a scale of 1 to 10. For example, the Marketing and Sales leadership at Ciena Network were able to integrate data from sales enablement and operations, marketing, and sales to create a dashboard that creates a dynamic and digital picture of what is going on in the account, according to Jason Phipps, the Chief Revenue Officer of Ciena Network“We are able to answer critical questions like – are we engaging at the right levels in the organization? And are those stakeholders attending webinars, participating in “Demo days,” or downloading materials? We’ve had to combine data from a variety of data sources showing how different players on our revenue team are engaging with the key stakeholders in the account – from CEO to engineering.”

The emergence of advanced analytics, AI, and Machine Learning (ML) – and the massive new sales engagement data sets to support them – represents the most significant opportunity to accelerate sales growth since the scale adoption of call centers (40 years ago), CRM (30 years ago), and digital channels (20 years ago) in sales.

Unfortunately, the majority of sales leaders are missing a big opportunity because they are not using the customer engagement data available to them to create advanced enablement, readiness, and measurement systems. The vast majority of organizations have the ability to mine and monetize this data, yet only a small fraction actually do – despite the hype around conversational intelligence. This is gold right at the surface.

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