Simplifying The Science Of Selling
How AI is Converging Sales Enablement, Readiness, and Engagement
A revolution in sales analytics and artificial intelligence (AI) is converging the sales enablement, readiness, and engagement software categories in ways that will make front-line selling faster, simpler, and more consistent. This confluence of capabilities represents a significant opportunity for B2B organizations to generate the next level of growth from their revenue teams. Senior growth leaders that configure these platforms in ways that make them simpler to use by sales, marketing, and customer success reps will realize the immense promise of this latest generation of selling technology.
A recent analysis by the Revenue Enablement Institute identified 100 technologies that are transforming the commercial model to make it more digital, data-driven, agile, and accountable. Over 90% of the platforms chosen from over 4,000 evaluated are using advanced analytics, AI, and Machine Learning (ML) to better enable sales, marketing, and CX teams.
Individually these innovators are connecting the dots across the sales and marketing technology portfolio to optimize resource allocation, direct revenue teams, enable individual sellers, measure, and motivate performance, and personalize communications, pricing, and offerings.
Collectively, this group of platforms are fast becoming the core components of a “Revenue Operating System” that turns legacy investments in sales and marketing technology infrastructure – and the customer data these systems create – into selling outcomes that grow revenues, enterprise value, and profits. This has led to a Copernican Revolution in sales technology that is blurring the lines between traditional software categories.
This revolution is forcing senior growth leaders to re-imagine their growth technology portfolios from the top down to better support the selling process and generate more revenues from their selling assets. This places a premium on platforms that can aggregate, orchestrate, and deploy customer engagement and seller activity data faster and better than CRM.
This transformation to a 21st Century Commercial Model is necessary because the proliferation of sales and marketing technologies in the growth portfolio is making it more complicated for sales managers, performance professionals and front-line sellers to leverage technology as a “force multiplier” in day-to-day selling. Many of the sales enablement and operations leaders we talk to cannot name all the solutions in their portfolio or explain how they are improving selling outcomes. Finance executives that take the time to add up their total technology cost per user are questioning whether the expense is justified. Most significantly, the revenue teams using these tools on a daily basis are stressed by dealing with too many disconnected “panes of glass”, information overload, and “tool fatigue.”
An immediate consequence of this “Copernican Revolution” has been the rapid convergence of sales enablement (sales guidance), sales readiness (sales training), and sales engagement (aka data-driven selling for lack of a better description) solutions into a platforms that better support front line sales reps. Historically these have been separate functions and processes that were supported by different solutions at different stages of the customer journey. To support modern selling these need to be forged into one selling motion concentrated at the moment that matters – a live customer interaction.
A big underlying reason the sales enablement, readiness, and engagement categories are converging is they fundamentally support the same selling activities and run on the same content and data. Over the last decade these categories have expanded and overlapped because they support the same day-to-day seller workflow – target, prioritize, prepare, engage, follow up, report, and repeat. These platforms also use the same content – playbooks to prepare for meetings, training to practice the skills needed on the call, and selling content to communicate with clients before, during and after calls. They also increasingly use the same data to run. All three activities are informed by customer engagement and seller activity data. Much of this data is now drawn from actual presentations and conversations by humans – from call recording transcripts, conversational intelligence, or practice demo presentations by reps.
This convergence has been brought to a tipping point by two trends:
- The mainstream adoption of AI in sales fueled by the emergence of massive new customer engagement, activity, and conversational intelligence data sets.
- And the dramatic shift to digital buying by B2B customers at every stage of the customer journey.
“An explosion of sales engagement data has become available to analytics teams in the past 24 months,” according to Len Ferrington, a Managing Director of Summit Partners. “This data is coming from first party systems, email, calendars, third party sources, recorded sales conversations (via Zoom, Teams or transcripts) and contactless selling platforms (like text and chatbots).” For example, the number of recorded sales calls recorded has gone up thirty fold since the start of the pandemic.
AI is increasingly being used to mine all this data to help reps make better decisions and help managers to evaluate training needs, selling priorities, and seller performance. The best organizations are evolving their use of AI to support Emotional Quotient (EQ) applications as well as the IQ of selling, according to Raghu Iyengar, Professor of Marketing at the Wharton School of Business. “The rapid growth of virtual selling is creating a need for AI and analytics that inform the EQ of selling to help sales reps better understand customer sentiment, response, and relationships in the absence of face-to-face conversations,” reports Professor Iyengar. “Businesses will need to find ways to use new data from customer transcription and digital engagement platforms like Zoom or Teams to understand customer emotions and all the non-verbal elements of selling.”
The shift to virtual selling and buying has also been a factor as customers demand a faster cadence, more complete answers, and more personalized content at every stage of the customer journey – regardless of whether they are talking to an account rep, BDR, product specialist or customer service manager. “As B2B buyers’ increasingly use digital channels and information in the customer journey, it is reshaping how B2B sellers engage with them,” according to Brent Adamson, Distinguished VP, Advisory, Gartner, “This presents a huge challenge to B2B revenue teams because our research tells us that most B2B buyers under the age of forty would prefer not to talk to sales and service reps at all if it was possible and they can see no difference in the digital buying experiences of most of the companies they try to buy from. It is going to be mission critical for reps to make the most of the moments that matter during this buying cycle.” That means building buyer empathy, sharing more compelling content, asking smarter questions, and having conversations that build trust, communicate the financial value of their solutions, and reveal the nuanced differences between their competitors.
To stay ahead of the competition, a new generation of growth leaders (CXOs) are finding ways to connect the dots across these solutions to create technology ecosystems that better support the customer journey and day-to-day workflows of revenue teams – regardless of whether they reside in sales, customer success or demand marketing. Specifically, the are combining platforms into end-to-end ecosystems that support the day to day selling process, integrated learning and development and data-driven sales guidance.
Many executives are trying to assemble and connect these different platforms themselves or with partners. Others are making bets on a handful of platform partners they can invest in for the long haul to become the technical and analytics backbone for the 21st Century Commercial model. Both tasks are being frustrated by confusion caused by the proliferation of point solutions to support selling and the rapid convergence of traditional software categories. The features and capabilities of many of these platforms increasingly overlap, and their roadmaps all converge on the same fundamental north star – data-driven selling in real time. On a practical level, the traditional categories most organizations use to evaluate, select, and configure software solutions fail to fully describe all they different ways solutions create value, or how they are connecting the dots across the sales and marketing technology ecosystem. Nor can they communicate the implications of this convergence on sales management, operations, and enablement organizations as they are increasingly integrated into a Revenue Operations model.
Senior growth leaders must force themselves to look past this background noise. CXOs must provide their sales operations and enablement teams clear strategic and financial criteria to help them evaluate, consolidate, and evolve their growth technology portfolios. This requires a “top down” roadmap for building a “Revenue Operating System” that generates more growth and profits from commercial assets – which include data, technology, content, and digital selling channel infrastructure.
To rise above this clutter and confusion, growth leaders should focus on four things as they try to simplify, streamline, and focus their sales technology portfolio on accelerating revenues in the new market reality.
- Rationalizing sales enablement, readiness, and engagement into a single end-to-end platform to create a closed loop feedback system that integrates planning and prioritization before the sale, with action and engagement with the buyer, to reinforcement and coaching after the fact.
- Turning customer engagement and seller activity data from across the sales and marketing ecosystem into insights that inform high value and complex selling interactions by sales, marketing, and CX teams.
- Do all these things faster – or in real time – at the moment that matters during the sales call to build buyer empathy, ask the right questions, start the right conversations, and demonstrate value.
- And making things simpler by finding ways to reduce information overload, multi-tasking, and the number of “panes of glass” front line sales and service reps must use to do their jobs.
A good example of a solution provider that is doing all four these things is ringDNA. Over the last 8 years, ringDNA has built an end-to-end platform that uses AI to connect the dots across the entire sales and marketing technology ecosystem to help front line revenue teams to prioritize, prepare, and execute effective sales calls. They combine customer engagement data from actual seller conversations with CRM, exchange data and third-party buying signals to create a complete picture of seller activities, behaviors, and conversations. And they integrate with other key assets in the growth technology ecosystem – CRM, sales enablement, videoconferencing – to share information and take advantage of insights generated in those systems.
Frankly, a lot of solutions say they do all of this, but in fact can only do some of this. The reason ringDNA is interesting is they represent an actual example of what this “future state” looks like in practice, which is why Gartner identified them as a leading platform for enabling Revenue Operations. ringDNA stands out because they’ve figure out how to use AI to synthesize big data into small data that gives sales managers a way to monitor and coach their teams at scale and provides customer facing employees’ actionable instructions and guidance at the moment that matters – in live conversations with buyers.
Unlike many promising applications of analytics to grow revenues, this one is not a “bridge too far.” Every organization has the fundamental data to get started – recorded conversations, content consumption by clients, CRM and exchange data from email and calendars. And any organization should be able to leverage this customer engagement and seller activity data they already have to pilot real time guidance and coaching at scale in 30 days if their CXOs demanded it.
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