5 Steps Toward A Data-Driven Sales Pipeline

Pipeline Management 101

Intuition doesn’t cut it anymore. Big data informs virtually every aspect of business, including the sales pipeline. But converting all that valuable sales pipeline data into action is where most managers get stuck.

If you use data to understand, measure, and valuate your pipeline, however, you’ll see significant returns. The best managers know the precise value of their pipeline and the opportunities within it. They also know how to avoid friction between the revenue and sales cycles and watch for trends. All of this requires data.

Here are some tips for putting evidence-based strategies into place for your sales teams. You can’t compete without them, and the transformation towards a more data-driven sales approach doesn’t have to be painful. Here are five tips to get you started:

1. Define and Document Your Sales Process

Most sophisticated sales organizations have adopted some sort of formalized selling process. Whether it’s Miller Heiman’s “Conceptual Selling“, SPI’s “Solution Selling“, or your own proprietary system, your processes must be defined, measurable, and consistent.

Observable Sales Milestones

As a baseline, you should:

  1. Understand and define the customer buying process
  2. Define selling steps that align to the buying process
  3. Identify key checkpoints and milestones that link the two processes together

Your teams not only need to be using the same CRM tools, they need to be speaking the same language, sharing the same goals, and utilizing the same KPIs.

 

2. Grade and Track Every Opportunity

Of course your organization will be more productive if you focus on the lowest hanging fruits – deals closest to closure versus those in the early stages. The key here is to develop a scorecard for sales opportunities and corresponding tracking mechanisms, alerts, and risk management tactics.

assign values scores to attributes

Steps to establishing a workable scorecard system include:

  1. Identifying the key phases of your sales cycle and assigning scores to each phase
  2. Assigning weights to scores according to their influence on success
  3. Defining the characteristics of your “ideal” sales situation

 

3. Kick the Meeting Habit

In a data-driven world, the old-school approach to sales meetings have little value. In fact, they can cost you thousands of dollars every month in lost productivity, and much more if your sales organization is large.

Sales Cadence Meeting Calendar

If everyone is marching to the same beat and utilizing data to guide their actions, the need (or perceived need) for meetings is greatly diminished.
While some face time is valuable, focus on streamlining interactions that, if left unchecked, can do more harm than good. Minimize the number of calls that include the entire sales force, for example. And never combine short-term discussions with long-term issues.

 

4. Get a Grip on Forecasting

Like most meetings, the Sales Forecast Call has become a wasted opportunity in many sales organizations. What could be used to make real process improvements is instead used as a reporting exercise. Here are a few ways to make the Sales Forecast Call worthwhile again:

  1. Ask the right questions:
    • How much detail is needed?
    • How can you manage risk and promote accountability?
    • Are your coverage ratios adequate?
  2. Align forecast call rhythms with those of your business
  3. Use your scorecard data to prioritize deal reviews
  4. Identify problems by tracking key measures over time
  5. Make teams accountable for actions they commit to
Sales Forecasting

 

5. Understand Your Revenue Cycle

You run sales – do you know how many leads it will take to feed a fully productive sales person? Do you know the right time to add the next sales person to your team? This is another area of management where real-world data will serve you well, and gut-level instinct can be costly.

Modeling your revenue timelines should include the following steps:

  • Establish baselines for the duration and size of your average deal
  • Identify all the key milestones in your business’ revenue cycle
  • Develop a formula for measuring conversion rates at each milestone
  • Monitor, learn, and continually adjust your model
Revenue Cycle Waterfall

Do you have any tips or best practices on building a data-driven sales pipeline? Please leave a comment!

Live Webinar: 5 Secrets To Closing More Deals Using Big Data Analytics. Register Now!
Swayne Hill

 

Swayne is the former SVP of Sales at Mintigo. He was previously Senior VP and co-founder of Cloud9 Analytics, a leading Sales Forecasting and Business Intelligence solution provider, serving Pandora, ADP, LinkedIn, DocuSign, EMC and many more. Earlier in his career, Swayne spent 13 years with Cognos building and running sales teams around the world as the company grew from $50M to almost $1B in revenue and was acquired by IBM. Swayne sits in several high-tech startup advisory boards and holds a Bachelors degree in economics from the University of Toronto.

1 Comment

  1. Marty

    Swayne, great article. We work with a lot of small businesses in mastering their tech. I feel like a lot of what is missing is a proper education on conceptually putting together things like pipelines. Too many people teach just how to use the tool rather than why one should use a tool.

    I found this helpful in establishing my own pipelines in my CRM too.

    Thanks for the clear and well structured article.

Leave a Comment