Importance of data in Channel Marketing

During our State of Partnership webinar, featuring insight from; Jay McBain, Chief Analyst at Canalys. Nicole Dezen, CVP, Global Partner Solutions at Microsoft and Tom Perry, CEO of Sherpa, data was a key topic.  

Nicole started by saying; “Data is the epicenter of everything. The challenge is unfortunately, it's a garbage in, garbage out experience. And so, getting data right within Microsoft is I consider to be mission critical.”   

When you consider we need to make these data-driven decisions at scales, the challenge only gets larger, as we have so many variables within Partnership Ecosystems. So, we need data to inform programs, the investments and then pair that with Partner feedback. Data is the science and the qualitative insight from Partners is the art.  

Tom supported this station “We are getting to the age of sophistication. Revenue is a lagging metric, however it’s easy, you know if you’re performing well because you know your revenue is growing”. A lot of the work we’re doing is working with Vendor data to look at leading metrics and propensity, looking forward at ability to grow.

The challenge with Partner data is it sits in four or five systems. We’ve recently built EdisonAI which looks at those disparate systems and using AI machine learning, brings the data together to generate a Partner score and place Partners in a quadrant.  

The work we’ve been doing the last couple of quarters to help vendors look at Partner marketing elements, Partner Marketing skill, alignment between vendor and Partner is very powerful. We’re using AI machine learning to organize this data and review alignment.  

We’re not talking about tiers anymore within programs, we’re talking about the Partners ability to grow. Understanding where we should invest, who we should support and where they are. Capturing external, internal and importantly feedback surveys as well to get a full view.  

Key takeaway - why is data so important to Channel marketing?

Nicole underscores data's crucial role at Microsoft, highlighting the importance of accurate data handling as mission-critical due to the "garbage in, garbage out" challenge. In navigating complex Partnership Ecosystems, combining quantitative data with partner insights becomes essential for informed decision-making. Tom notes the shift towards sophisticated data analysis, beyond just revenue metrics, to predictive indicators of growth potential. The introduction of EdisonAI, leveraging AI and machine learning, synthesizes data from disparate systems to assess partner performance and alignment comprehensively. This strategy focuses on identifying partners' growth potential and investment areas, moving beyond traditional tier evaluations to a more nuanced understanding of partner capabilities and alignment, informed by both data and direct feedback.  

How to start you Channel data journey?

Data transformation doesn’t have to be a companywide initiative that takes millions over years. You can start small. EdisonAI will do this at a fraction of the cost, informing you on the state of your data, growth potential and where to invest to drive Partner ROI.