Creating A Data-Driven Sales Process

May 24, 2016 Richard Bayston

When businesses scale faster than their sales departments or their budgets possibly can, a solid sales process is the difference between liftoff and stalling revenues.

Sales processes should give each salesperson - AE, SDR, whatever their role - a clear idea of what they should do, as well as when they need to pass the baton and when they need to stand ready to catch a pass from someone else.  At the same time, it should give C-suite a clear overview of the whole sales roadmap. What we’re talking about is structuring sales behaviors to fit the funnel.

Yeah, about that.

Funnels always were more of a metaphor than a reality. In a SaaS world where buyer journeys are increasingly non-linear, funnels are an increasingly obsolete metaphor. Instead of using a convenient mental picture to map your buyer journey, you need something reliable, solid and definite.

You need to build your sales process and your buyer journey map on data and understand how that data informs your actions at every stage.

 

Track Data

tracking data

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Salespeople hate to track data. In fact, they hate to do everything except sell. That’s understandable when you get commission on sales, not data entry, creating content, or staring at charts. But sales process creation and optimization is an investment in future sales. Done right is pushes sales forward and frees reps up to sell. Everyone gets better numbers and everyone gets better revenue, including reps who see their commission rise.

Building a data-led sales process means having access to company-wide data, but specifically tracking sales data. After all, marketing data stops being useful at the point marketing hands a lead on to sales. Ask Zendesk.

When Zendesk went public, writes Lauren Horwitz for TechTarget.com, their traffic exploded. But their sales didn’t. One of those metrics has marketing jumping for joy, the other has sales reps hopping with frustration.

Sound familiar?

Zendesk’s director of global sales, Stephan Blendstrup, frames the problem:

‘The number one thing I want to know is why aren’t my leads converting into sales?’

That’s where a data-led sales process should be able to both answer the question and solve the problem.

A solid data led sales process should be able to pass leads on to sales either from SDR of from marketing that are highly qualified. And it should let you know what to do at every step to move those leads to purchase.

The only way to get there is to track all your day to day actions so you have some data to work with. Otherwise you can’t know what the best practice for each situation actually is.

 

...And Use It to Identify KPIs

Using data isn’t the same thing as tracking it. Most organizations have literally more data than they know what to do with. Yes, much of it isn’t the information they actually need to base effective decisions on, but they also lack a system for analyzing and acting on what they have.

The first task when analyzing data is to figure out which numbers to track. Yes, record everything - but if you look at a hundred different metrics every day and try to figure out what they all mean you’d be even worse off than just taking a guess. What businesses need is to identify their KPIs - Key Performance Indicators.

Department-wide KPIs might include things like the number of dials each rep makes a day, the amount of time they spend on the phone, how many new leads they have in a week. They’re all common numbers used to track efficacy. The main point is that we’re looking at process, not outcome. Tracking revenue doesn’t tell you how many revenue-producing actions your staff is taking at a sufficiently granular level.

KPIs need to be understood - not just known - by everyone on the team. Everyone needs to know why they’re being tracked and understand the importance of using them as a tool to measure success. That means they need to be tracked openly, too. There are a ton of tools available to visualize KPI performance. But better a line on a whiteboard backed by a solid team-wide understanding of why it matters, than a gorgeous dashboard no-one cares about because they don’t know why they should.

In selecting team or department-wide KPIs, there’s a risk that managers neglect to identify weak points in their team members. Identifying personal KPIs for staff members can be time-consuming, but it can also radically accelerate sales. It’s a key part of the drive to increase rep productivity and leverage the value that the middle 60% of performers are sitting on and don’t know how to access.

 

Stack The Tech

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Constantly reinventing the wheel used to be a staple of bad standup comedians, who would observe that they now had at least four copies of the White Album - on vinyl, CD, MiniDisc, MP3 and so on. Aside from recognition, the skit plays on the idea that progress is a fake and the MiniDisc version isn’t really better the vinyl.

OK, I’m going to back away slowly from that contentious point, but we all know that business technology has enabled very real progress. You and your laptop can do things that used to require literally dozens of full-timers. And new business tools can do things that couldn’t be done at all twenty years ago, whatever the resources at your disposal. That frees staff up to create more value.

But it creates obligations as well as opportunities: it means we have to stay current or lose out to competitors who are leveraging technology effectively.

None of this means it’s a good idea to take every upgrade. But it does mean you should be level with industry standards. And technology that lets you engage with data and learn from it should be on your to-do list.

You should be looking at tools and evaluating them, sure. But you should consider joining the two-thirds or more of sales firms that are moving toward more sales technology over the coming year, in response to challenges that include a growing influx of data as well as the desire to more accurately and effectively analyze the data they already have.

Desiloing data in terms of departments is vital too. If marketing has one set of tools, one body of data and one definition of ideal customer, while sales is using totally different information, tech and criteria, it’s no wonder that the leads are weak. (Yeah, I went there.) On the other hand if sales and marketing can access the same data and agree on the same definitions, there’s a better chance of aligning the whole enterprise around actionable data. But the only way to do that is if everyone is using the same, or at least compatible, tech stacks.

 

Active, Granular Analytics To Power Effective Lead Nurturing

Tracking revenue is important but it makes more sense to track the figures that get you revenue. We’ve covered that already, and I hope I convinced you if you weren’t already up to speed.

Those numbers themselves can be broken down further and cross-referenced to give more accurate pictures of prospects’ behavior and reps’ actions and the relationship between the two. It’s the same idea, a level down.

For example, cycle length is a vital piece of information. How long does it take for the average deal to go from the top of the funnel to purchase?

Trouble is once you know that, what can you do with it? It’s hard to know how to shorten the sales cycle without having any insight into what makes it the length it is.

That’s where active analytics comes into play. You want to analyze the data you have on a step-by-step basis. Which sales cycle phases are leads spending the majority of their time in? What kind of lead becomes a permanent resident of the sales cycle, never advancing to buy, and what could you do to move them onto the next step?

Once you have that kind of information you can begin to construct segmented funnels-within-funnels that progress leads toward purchase in a way that’s supported by the evidence. Let's say, people who download an ebook but not a white paper don’t usually wind up buying. When someone downloads an ebook, drop a task into a rep’s to-do: contact that person, offer a chat - and gift them a relevant white paper.

 

Conclusion

Building a data-driven sales process has to be a part of a change across the whole organization, a pivot toward alignment based on analysis of customer and internal data. Within the sales department, it’s crucial to isolate the metrics that really need to be tracked and tie them to rep performance and team success. Customer data should be used to create an accurate map of lead responses that allows you to predict and control the sales process as much as possible.

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