It is no secret that technology has upended B2B sales — and in our current environment, in particular, the use of technology and data is more critical than ever. Generic outreach does not cut it anymore; on average, buyers answer just one in 18 sales calls and open one in four emails. In a virtual selling world, the stakes are even higher. Sellers cannot afford to take a scattershot or uninformed approach; they need to reach the right lead at the right time with a differentiated and valuable message. Doing so at scale requires a new focus on quality — not volume — of outreach. It also requires data.
For the last nine years, I have seen this shift while leading teams at LinkedIn and partnering with businesses across the globe. In McKinsey’s 2018 Global Survey, nearly half of senior leaders said that data and analytics “significantly or fundamentally changed” their sales function in the prior three years.
Skill sets have also evolved: LinkedIn research reveals that “data analysis” appeared in sales professionals’ profiles three times more in 2019 than in 2015. The report also found that top-performing salespeople (those who reach 125% of their quota or above) are more likely than their counterparts to consult data — for instance, by applying patterns from closed-lost business to improve future win rates.
Insight Center
A data-driven sales organization can create value for nearly every business function, from marketing and customer support to product and corporate strategy. Leaders need to recognize this trove of untapped insights — and take steps to put sales data and analytics into action across the organization. Here’s how.
Close the Data Gap Between Marketing and Sales
Aligning Marketing and Sales is notoriously challenging precisely because of the data. The first challenge is to get the right data sets: four in five salespeople identify a significant gap between the data used by Marketing and Sales. What’s more, data quickly becomes stale as stakeholders move companies and roles, which one in five decision-makers do during the buying process.
However, feedback from Sales on behavior throughout the buying process can help Marketing to more effectively qualify and target leads. Additionally, accurate and up-to-date CRM data can help Marketing teams refine their buyer personas by painting a higher-fidelity picture of the buying committee.
Gain First-Hand Insight from Buyers
In enterprise software and many other industries, sales reps tend to have deep relationships with their customers. Sales conversations, therefore, tend to be a source of rich insights about gaps in the product and objections to pricing structures, among others. With today’s machine learning and speech analytics tools, it is possible to analyze large volumes of calls, then funnel feedback to the product and pricing teams.
We tap sales insights to help us understand where and how our customers perceive value, which guides our product roadmap. For example, after customers expressed the need for metrics to communicate ROI within their own companies, we built more self-service analytics and reporting capabilities into our product.
Segment and Prioritize Accounts Based on Customer Metrics
Sales, Customer Support, Marketing, and Product teams can all benefit from insight into which accounts are poised for growth, which are ready for cross-selling, and which are likely to churn. For instance, churn metrics, support ticket themes, and product usage patterns can shine a light on product-fit issues and renewal risks. This insight can drive marketing campaigns or commercial offers that compel customers to stay or engage differently with the product.
Metrics such as retention rate and customer lifetime value (LTV) can also inform how Marketing invests in acquisitions, upselling, or cross-selling. A company could segment its customers and invest in marketing additional product offerings to existing healthy customers. It could also learn from what types of customers tend to have a higher or lower LTV, and adjust acquisition efforts accordingly.
Identify Growth Opportunities Through Momentum Signals
At a macro level, insights gleaned from sales data can help businesses shape their growth strategies, focusing on entirely new segments of a market or moving away from unprofitable areas. Within specific accounts, business momentum signals — like hiring, raising capital, or opening new offices — can shed light on an increase in the total addressable market (TAM). Today, most organizations look at customer relationship management (CRM) data, such as contract size, to identify potential account growth. But, current spending may only give a limited view; a company that just closed a big fundraising round, for instance, may have a larger TAM than its current contract suggests. Looking at data from a different angle can help to spot momentum signals as they happen.
We used to assign accounts at LinkedIn based on current, plus potential, spend. We are now starting to reorient around where customers are in their lifecycle of adopting modern selling. This approach allows us to better align our cross-functional investments — like Customer Success, Marketing, and Insights — to support customers where they are and help them get where we believe they could be. For instance, we advise our team to prioritize companies that have strong sales enablement and sales operations functions; we find that these accounts tend to most quickly implement behavior change and have a propensity for faster value creation. If companies don’t have these functions, we’ll advise them about the role that sales enablement and sales operations can play in building a more effective sales organization.
Looking Forward
In the months and years to come, companies will need to focus even more on solving their customers’ biggest business problems and proving their value over the long term. This shift is good news for data-driven organizations, but can be a challenge for those who are not yet harnessing their data to deploy their sales teams against the right opportunities. It is time for leaders to guide their organizations down a data-driven path that starts with sales and extends throughout the business.
