B2B Sales Data.

B2B Sales Data.

Founders are usually ‘data driven’, yet they are doing not look at basic sales data.

At the outset, let’s explain what we mean by basic B2B sales data. There are two broad categories of sales data points that a corporation must have:

Visibility into B2B sales funnel

1. A number of deals are being created at the highest of the funnel & progressively moving to subsequent stages ( Opportunities, Proposals, negotiations, closures etc.)
2. Conversion rates across each stage of the funnel
3. Conversion rates supported the source of the deal ( Inbound, outbound, referral, etc)
4. Time is taken in each stage of the funnel
5. Lost reasons for every stage of the funnel

Visibility into B2B sales performance

1. Target vs Achievement ( Revenue & # of deals)
2. New business vs repeat business
3. Product wise achievement
4. Performance against input parameters like deals created

We speak to tech-focussed companies for his or her B2B lead generation. Founders of those companies often come from a strong product or tech background. When it involves discussing B2B demand generation, however, we discover something very counterintuitive in their narrative:

• Sales data is either completely absent or poorly captured
• Their views are mostly derived from anecdotal evidence
• Sales achievements (over/under) are usually attributed to the sales team

We found it odd that folks from data-driven fields like product & tech completely abandon that thought process when it comes to sales. We spoke to some of them to understand why that might be so.

Why do founders recoil from a data-driven approach to sales?

Sales data is tough to capture

Unlike data associated with user metrics or online spends, sales data is far more difficult to capture. One has got to almost entirely rely on salespeople to create useful & accurate sales data.

Most organizations simply buy a CRM system in the hopes that the sales team will enter data. After some unsuccessful attempts, the system is abandoned and they revert back to focussing on immediate expected closures through excel sheets.

Sales data is harder to interpret

Sales performance is usually impacted by a multitude of factors both external and internal. a replacement marketing campaign or a drop in prices could impact sales, so could any action by competition or a general change in economic environment.

In the real world with clients, it’s often difficult to make perfect data sets to derive clear insights from sales data. This inability to derive easy actionable insights from sales data makes organizations abandon the exercise completely.

Sales data is straightforward to manipulate

Sales data is eventually the sales person’s estimate of what the client is thinking. Salespeople are likely to urge this wrong occasionally. some are also likely to misrepresent data points intentionally to save face. this is often fairly simple to catch for seasoned sales leaders. whether or not it isn’t caught immediately, it can rarely go unnoticed beyond some weeks. However, most organizations lose faith within the system prematurely and abandon the system completely.

Long sales cycles imply considerable lag in data

B2B sales usually have long sales cycles. Any change you create is likely to take effect further down the line in the future. One must be patient while analyzing sales data and ensure you’ve given it sufficient time.

For organizations want to see immediate impact of initiatives in other fields like online spending for example, expecting a few weeks to understand the effectiveness of changes they’ve made does not seem worth the effort.

Top performing salespeople often mask underlying issues

Finally, all organizations always have top-performing salespeople. These rainmakers had best in spite of lacunae in the sales system. While one should be on the lookout for such sales reps, that can't be the basis of building a consistent & predictable sales engine at scale.

Unfortunately, it's easier for organizations to believe that getting more such people is a better way to tackle faltering sales rather than investing time in fixing the process

Our view

There are indeed several challenges in getting reliable sales data and actionable insights thereafter. this will be overwhelming for most startups.

However, the choice of scaling up without sales data can be catastrophic. One can paraglide without a navigation control. Does that mean one can fly an outsized aircraft without navigation? That is what people are attempting when they try to scale businesses without sales data. it's bound to fail.

Moreover, the challenges mentioned above are often overcome by appropriate sales design. Startups could be building sales systems for the first time, but sales as a function has existed for many years and centuries.

There is a wealth of knowledge out there about designing the right data capturing systems, and processes to make sure adoption and interpreting of sales data. it'd be wise to not reinvent the wheel and learn from some of the existing best practices around sales.