By John Bara, CMO, Mintigo
I have been through multiple mergers and acquisitions in the software industry. In each case, business models depend on successful cross-selling of new products and services to respective customer bases of the newly combined companies.
Have you been a part of a merger or acquisition? Was the newly combined company pleased with the results, or did they disappoint? What was the success rate of finding existing customers to cross-sell the newly acquired products or services? How were those targets selected?
By John Bara, CMO, Mintigo
I have been through multiple mergers and acquisitions in the software industry. In each case, business models depend on successful cross-selling of new products and services to respective customer bases of the newly combined companies.
Have you been a part of a merger or acquisition? Was the newly combined company pleased with the results, or did they disappoint? What was the success rate of finding existing customers to cross-sell the newly acquired products or services? How were those targets selected?
With a few notable exceptions, my experience in cross-selling was almost universally disappointing in almost every merger or acquisition. I believe the lackluster results have little to do with the merger being a strategic misfit or a lack of sales execution. Rather, the results are the due to poor targeting.
The problem begins with an unscientific targeting process. Typically, company A acquires company B. Company A, the bigger company, ingests the employees of company B and forms a group chartered with cross-selling company B’s products to company A’s customers and vice versa. Sales teams gather and produce lists of targets for the cross selling. The sales results are almost always below expectations because the targeting is done without data to justify the target selections.
Enter predictive lead scoring, a data driven approach to discover your ideal customer’s DNA, target the customer and engage with the best message and channel. Predictive lead scoring is a perfect antidote for sub-par cross-selling after a merger or acquisition.
Instead of sales teams slamming together target lists via the “aerial extraction method,” the targets are identified by the distinct buying signals in the data that prescribe which customers are most likely to buy.
Post merger or acquisition, it becomes difficult to match the right product to a customer. It’s tempting to simply market everything to everyone. If only you had an easy way to match customers to the right products, you could focus your marketing, increase conversion rates, and unlock the value hidden in your customer database.
Today, with advances in Big Data there are tools which helps you analyze your marketing automation and/or CRM data to discover a distinct customer profile for each product. This enables you to then assign a predictive lead score to each prospect in your marketing funnel for each product.
As a result, you’ll know which products fit which customers and you can provide the most relevant offers and messages in your campaigns. Thru the use of predictive lead scoring, mergers and acquisitions can truly meet the strategic objectives of boosting revenue thru cross selling based on data driven techniques.
John Bara specializes in fast growth marketing with over 25 years as an executive in Silicon Valley. Prior to Mintigo, he held CMO and VP of Marketing roles at companies such as Thismoment, XenSource (acquired by Citrix for $500M), Interwoven, and Genesys Telecommunications Labs (IPO, acquired by Alcatel for $2B).
