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Using Analytics for Sales: Internal Data Highlights External Sales Opportunities

Using Analytics for Sales: Internal Data Highlights External Sales Opportunities

Crafting a good sales pitch can be difficult. Getting the right data, hitting the right client pain points, crystallizing why your services are better than the competitors, all takes hard work. Honing your sales pitch to an art takes time, and even with a perfect picture, new clients take time to acquire. One of the best ways we’ve found to build a good sales pitch is to use data you already have.
In the digital world, there is no shortage of data, which translates into no shortage of potential competitive insights and advantages. With databases, data warehouses, corporate intranets, best practice sharing, web analytics, voice of the customer information, and QA or Six Sigma data, you are well-poised for discovering good information.

Finding ways to mash those together into meaningful new understanding is the key. Here’s an example of an analysis we performed for a client. They wanted to know how they could meet more of their current customers’ challenges. This would result in higher client satisfaction, increased revenue (from cross-sells), and could help them in future sales efforts with potential clients.

We took their entire list of current clients and added the following data:
• Industry
• Number of employees
• NAICS/SIC code
• Site locations with latitude/longitude coordinates
• Number of times they had been serviced (grouped by dates)
• Customer satisfaction survey data

This gave us a holistic view of challenges faced by specific industries. To obtain this, we used data from our client’s data warehouse as well as used LinkedIn, Yahoo Finance, Dun & Bradstreet databases, Client websites, and social media. Doing this definitely took work, but it highlighted thousands of dollars worth in future revenue and client retention. See a portion of the analysis below.


This graphic depicts problems our client's customers faced.  The customers are grouped by industry.

 

For example, we quickly saw that the challenges faced by the banking industry were different than those faced by the inorganic chemicals industry. But we also saw that the challenges within industries were relatively the same. All the chemical companies struggled with the same things.

Using insights like these, we were able to pinpoint those clients who were lagging behind their industry peers in dealing with a certain challenge. This created cross-sell opportunities for our client. They were able to take the data and highlight these problems to their customers and show how their solution was solving similar problems for other members in the industry. This not only improved revenue, but also will increase customer satisfaction scores, as well as create more focused sales opportunities in the future.

Similar insights and opportunities are lurking in your own data. You just need someone to unlock them for you.

What do you think? Using the same data, what other ways could it be analyzed to find insights? How have you found insights in your own corporate data? Share your story.