RA Quick Insights: Mistake in Customer-Facing Analytics Solutions

I often see Manufacturers and Wholesalers making the mistake of trying to revolutionize entrenched Customer habits vs. creating easy-to-use, pragmatic analytics solutions that Customers understand and care about.

Customer-facing analytics initiatives can be a tremendous Sales Growth enabler for firms and enable a Company to charge higher prices (if they're delivering incremental, differentiated value). 

Analytics solutions for customers can take several forms, including:

1. Embedded analytics: leveraging existing transactional, zero- and first-party data to provide critical insights to your Customers as part of their daily workflow in your core software/platform offering.

2. Standalone SaaS offerings: providing key functional insights outside your core offerings in a distinct SaaS platform.

3. Actioned analytics (intelligent automation): this goes beyond providing metrics and actionable insights and focuses on executing on behalf of the Customer. Example: Manufacturers automatically replenish inventory for wholesalers and retailers based on order and sell-through patterns, demand forecasts, etc.

4. Data-Driven Consultative Selling: similar to 1-3, but instead of self-serve analytics for Customers, the Company's sales force has access to Sales Growth Analytics tools with key market insights and Customer profit/assortment optimization capabilities. The sales team leverages these tools to help their clients improve operating efficiency, revenues, and profitability.

However, there are several missteps we make in developing these Customer facing analytics solutions:

1. We rely on internal experts to develop the tools vs. co-creating with customers. It often yields over-engineering and complexity vs. pragmatism and simplicity. Most importantly, it creates analytical solutions that don't solve real customer problems - or at least not how customers like to think/act.

2. We underestimate the effort required to change fundamental customer habits in traditional industries (think mostly anything non-tech).

3. We overestimate the analytical sophistication of our Customers and Sales Force (RE: Data-Driven Consultative Selling). Beyond analytical acumen, Customers and the Sales team also have limited time to engage with complex solutions that require more than 1-3 clicks for actionable recommendations.

4. We often try to go big by developing future-ready Embedded Analytics or Standalone SaaS offerings that Customers (or our Sales Force) are not ready for. We embark on a strategy that requires heavy investment and a multi-year roadmap without having developed the foundational analytics DNA in our organizations and with our Customers.

An experienced Sales VP once quipped about a complex Customer Profit Optimization tool developed for his sales organization:

We want our Customers and Sales Force to do 360 reverse windmill dunks without proper conditioning, dribbling, or shooting skills. 

Remember, our Customers don't care about ML or AI. They want to make better decisions faster. If an Excel- or Power BI-based tool does the trick, so be it!