Demand generation teams, Revenue Development teams, AE teams, and CSM teams comprise the modern Revenue organization. While they engage with prospects and customers in different phases of their life cycle, collectively they are responsible for customer and revenue growth.
Data driven revenue teams strive to achieve and exceed growth goals with predictability and efficiency. These goals are connected to output metrics like Bookings, Revenue. In addition to these, there are 87 other essential KPIs that should be tracked but rarely are — why? Because analytics teams have a backlog a mile long and business teams can’t get these KPIs built…
BHAM stands for Business Health & Activity Monitoring. I’ll explain what this means in a bit. First, let’s recap how revenue teams currently use data to hit quarterly goals. The 3 weapons in the arsenal today are:
The state of the art in Business Intelligence is humans understanding business health by looking at dashboards, often in weekly or monthly business reviews. Tableau, the leader in this category captures this paradigm perfectly with its tagline: “We help people see and understand their data”.
But this approach is not human centric. Here’s why.
Before starting Falkon, I interviewed over 46 data and analytics teams to understand their day to day workflows. One of the most important things I learned was how much confusion exists about what metrics are.
“We have lots of dashboards to do reporting. Those are our metrics.”
This was a common and scary thing I heard repeatedly.
Metrics aren’t just dashboards. They are the foundation of an OKR driven company and without them “test and learn” is guesswork at best.
That’s why it’s important to understand what they are and why you should care.
Before getting into the generalized definition…
I used to run the Zulily store team. As a low-margin high-volume business, operational rigor was essential for us. We looked at dashboards every day and made rapid decisions about inventory, pricing, and marketing to capture customer demand. I loved how data-driven the company was. At the same time it was extremely painful to get the kind of operational visibility we needed from our dashboards.
Our solution: Line up an army of analysts to dive for explanations and answers in our data warehouse every day. This always bothered me. …
Previously, I wrote about the lack of intelligence in current BI tools. Looking forward, what are the traits of a modern BI platform that truly delivers on the promise of intelligence?
This modern BI platform understands concepts like Sales, Churn, Upsell, Leads, Opportunities, Deals etc. Therefore it can immediately offer deep insights, no human coaxing required. For instance, it quantitatively understands that churn and sales are inversely related and is able to quantify that for the human decision maker. It understands that all steps in a funnel are connected. Therefore instead of offering step-specific numbers, it is able to contextualize…
The Big Data wave has done exactly what it promised — landed dunes of data at our doorstep. Clickstream data, shopping data, customer support data, app usage data, user engagement data, email and ad clickthrough data…you name it, we have it. While there’s a continued appetite to collect even more data, we are grappling with our inability to extract intelligent, actionable information from the data to run our businesses.
Having been an operator and advisor at several B2C companies, I’m always amazed by the lack of insight relative to the volume of data being collected.
The three prevalent tactics companies…
Next step: Talk to some customers to understand if it’s actually great. Do some market research to see what else is out there.
If this is a consumer idea, doing the research is simple. Run an ad campaign on Instagram. Talk to family and friends. Lurk around where your customers hang out, and then approach them. Run a survey. Search for similar ideas on Google or in the app store. Try out competitive products by signing up (which is usually free). All pretty simple.
However, if this is a B2B idea, doing the research is not for the faint of…
6 months ago I finally decided to start my own company. I knew the team and culture I wanted to build, and the value I wanted to create.
I just needed to figure out The idea.
Many founders I spoke with shared that their idea came from existing domain expertise, or from deep passion. I couldn’t relate since my experiences & interests are varied. Through trial and error, I’ve learned that it takes at most 7 days to weed out obviously bad ideas, and years to craft a great one. …
Startups. Big tech companies. Product person. Entrepreneur. Cofounder Falkon. Lover of cats, dogs and novel ideas.