This is the fifth article in a series titled “five critical questions every channel chief should ask him/herself” and it addresses channel analytics. BI and Analytics are hot topics in practically every industry. Business users recognize that they need to do more with information to make better business decisions. This is certainly the case with channel executives in technology channels of distribution.
But why do we, as channel managers, still lag behind regarding the use of intelligence and data to make informed channel strategy and investment decisions?
When discussing this with channel managers of small and large tech companies there are a number of barriers they are still struggling to overcome:
- Disparate and inaccurate channel related data often present a barrier for small and large technology companies alike. Channel opportunities and revenue data are often kept in CRM. Program and funding data are maintained in a PRM system or on spreadsheets. Partner payment data is often maintained in the Finance department. There is no single source of truth nor ownership of (accurate) channel related data
- Channel management and other stakeholders such as Sales, Finance, and Marketing can’t agree on a common set of KPI’s to measure channel performance and CROI
- Another challenge often cited by large technology companies is that the corporate IT and/or BI teams will not let channel managers evolve as far and as fast as they want to. Nor do they necessarily understand the unique analytics needs of a channel environment
Data driven channel management or “Channelytics” is a big topic. To address all of the issues and discuss best practices would require far more than one blog article. For now, let’s focus on two topics:
- How to develop and maintain a single source of (accurate) channel data
This process starts with the Identification of all relevant sources of data, from distributor sales out data and partner master, to product master and product sales records, to channel program performance. The next step is to aggregate data, identify workflows, and to link those sources. For example, many technology companies do business with multiple distributors and receive sales out reports from those distributors. These reports will need to be “scrubbed” and aggregated to provide one master record of channel partners and revenues down to the product level. You must also be able to identify participating vs. non-participating partners for each channel program and so on. Finally, A QA process must be in place to scrub the data and maintain accuracy.
2. What to measure
Establishing a sound channel analytics practice takes a lot of work, expertise, and collaboration. But before you get buried in the “how” consider the “what”. The “what” is about optimizing program investment, increasing CRO, and increased partner and program performance. What if you could make even a marginal improvement in the effectiveness of your program spend and improve revenues with the top 10% of your tier two partners?
The key is to Identify programs and partner segments where benefits are effective and ineffective:
- Reduce or eliminate investments for specific partner segments and/or program benefits where ineffective
- Shift financial incentives between customer segments, attributes, and programs to increase performance and optimize investments
- Identify and prioritize partners with the greatest potential, and align your resources accordingly
- Grow your sales by continually refining your programs
- Make the 95% of your GTM program spend smarter
Common channel analytics methods include:
A matched-control vs. analysis group methodology is used to assess the impacts of programs or Incentives individually and in aggregate on sales revenue for participating and non-participating partners.
Pareto and RFM (Recency, Frequency, and Monetary Value) analyses are often used to segment partners in 20% brackets from highest to lowest value. Most recent, frequent, and highest revenue per partners are the most valuable partners.
Last but not least, in order to develop a best practice channel analytics practice and enable your company to make data driven channel management decisions you need:
- The expertise, processes, and technology to make it happen
- Senior management commitment to prioritize and fund the effort
- Consensus among finance, sales, marketing, and channel teams to execute on an agreed upon strategy