We have arrived at a time when data is finally treated not as a technical thing but as a business asset with inherent value. Business leaders who are not tech professionals now understand how powerful data can be when harnessed and applied. Technologies for processing, analyzing, and delivering insights and analytics have progressed in leaps and bounds.
So why are most companies still stuck in a data landfill? They have plenty of data, but it analytics are disorganized and most data just sits there, unused. Forrester says up to 73% of data is never even touched for analytics. While the limits of what is possible expand rapidly, execution is not keeping pace. Most business leaders I know have ambitions, a vision, and plenty of data at their disposal — but get stuck trying to bridge the gap between current state and their goals. Plus, data creation is increasing exponentially, making the situation worse.
Companies are stuck in this state because traditionally data efforts are aimed at improving operations — looking internally. This kind of effort is typically characterized by connecting all your operational systems, combining data into a big data warehouse, and putting a BI tool on top to produce reports. Management uses these to analyze operational performance and seeks to incrementally improve performance. These are usually large, expensive, risky projects that take a long time to realize any return on the investment.
Contrast that with customer-facing analytics — efforts targeted at your customers or users of your service. These have a broad audience, can start small, and differentiate your product from the competition. By differentiating an offering which involves analytics your customers care about there are immediate effects to top line revenue. I’ve observed these companies increasing win rate, growing key accounts, and improving customer retention.
What does a customer-facing analytic look like? Often it can be simple visualizations that answer questions your customers care about. Are they using your service efficiently? Are you delivering on your SLAs or promises? Can you provide some strategic insight?
Here is an example from HubSpot, which allows their users to go beyond tracking individual leads into understanding their sales funnels as a whole and spot trends:
LinkedIn proves that dashboards aren’t always necessary, with a single chart to help understand traffic to a company’s LinkedIn page:
My favorites are subtly embedded analytics or visualizations, tucked into the application itself rather than as a stand-alone dashboard. Here is another example from LinkedIn, showing immediate feedback on posts and other actions a user takes:
Of course, customer-facing analytics go well beyond visualizations. Ultimately, if you can answer important questions for your customers using visuals, predictive algorithms, in-person discussions, or plain old excel exports, you are going to improve your relationship with them and their dependency on your product or service.