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Top 10 Tips for Building a Sales Intelligence Program

By Dave Egloff | October 06, 2020 | 0 Comments

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It has never been easier to build a sales dashboard. Technology has made the painstaking processes of data transformation and visualization simpler and more accessible to savvy business users. Because of the ease, sales operations are producing an increasing number of reports and dashboards. Unfortunately, many sales leaders struggle as the increase in reporting has not led to an abundance of insights.

The need for insights has never been greater. Sales analytics has become a critical element of cross-enterprise decision making. See the survey data from Gartner research that shows the percentage of cross-functional groups that consume sales analytics.

Savvy sales operations leaders recognize the organizational needs and opportunities, and many are formalizing a sales intelligence program to evolve from merely “business as usual” reporting. Here are ten tips in building a sales intelligence program:

1) Lead with a business purpose

Sales intelligence is not about technology. The goals are to understand the health of the business and inform decision making. Essentially, you want to give business leaders a new perspective on their business and help them take action.

2) Have an executive sponsor

The best executive sponsors are those that are intellectually curious, data-oriented, and open to new ways of thinking.

3) Work incrementally — quality over quantity

Start small and iterate. Collect early (and visible) wins but recognize that you will stumble through unforeseen challenges – internal politics, data hygiene, technical woes, etc. Also, while it is tempting to deliver many dashboards quickly, it is better to deliver fewer, meaningful insights.

4) Start with a top-down approach

Top-down approaches cascade from the organization to the sales team to individual sellers. The top-levels (e.g., organization and sales team) are often an easier place to start. While a bottom-up approach has value, idiosyncrasies at the lower levels may cause delays.

5) Lay out a roadmap

Let key stakeholders know how your insights will impact the business. Identify near-term deliverables focused on business problems. Also, calendarize your business cadence with an illustration of how insights can improve decision making or planning (such as territory design, account segmentation, quarterly business reviews, etc.).

6) Be clear about the scope

When it comes to sales intelligence, there is value in providing transparency to data, analyzing the data to deliver insights, and being part of the transformation to improve performance. Be clear with your stakeholders on your scope and focus. Manage their expectations.

7) Build a virtual community of early adopters and key influencers

Assembling a virtual team to promote diversity in thinking, increase usage, and improve data-driven decision making. You may also want to consider creating a cohort of citizen data scientists. These are functional practitioners across your organization that are business and data-savvy and capable of applying data-insights despite not being classically trained data scientists.

8) Measure stakeholder consumption and manage perception

Success comes from how insights influence leadership and decision making. If insights are not being used or leveraged, figure out what needs to change. It might be something quite simple.

9) Focus on insights consumption

Deploying analytical insights is as much about people change as it is about a technology change. Help sales managers and leaders understand the data and insights. If needed, teach them how to consume these new insights.

10) Be a data master

Being a master of anything is simply cool. So, to become a master, continually be aware of your data sources, data hygiene, and mechanisms for collecting data in the future. Data is the lifeblood of your sales intelligence program and is the key to sustainable success.

Sales intelligence will dramatically improve decision making. The idea isn’t to replace business acumen or intuition. Instead, it is to empower decision-makers by organizing disparate data to become information that leads to actionable insights.


*** Please note that this is an update of my January 2019 blog of the same name ***

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