In the early stages of my career working for a large Dow 30 company, I was schooled with the notion "Hans, you need to know your numbers". Throughout my career, this advice has stuck with me. As a small business owner, my focus has been on cash flow and liquidity. When co-managing the Profit & Loss and Balance Sheet of Vendemore it has been about revenue, costs, deferred revenue, pipeline, EBITDA and EBITA. Numbers have meant different things at different stages of my career.
It has been six years since I started working in the Account Based Marketing (ABM) arena. For most of those years, I have engaged with senior executives, sales and marketing professionals from C-level down to in-country field team-members. My engagement has mostly been with Fortune 500 companies in the tech space. Until two years ago, I focused exclusively on activating sales and marketing against these clients' account lists. I assumed incorrectly, that these account lists had all the internal and external data (numbers) to make the wise investment decision to pursue. However, it has become increasingly clear to me that the real business issues are not about the best Return on Investment (ROI) on marketing spend, best marketing & sales mix, what sales coverage model you deploy, or if your sales & marketing functions are 100% aligned. They come later. It is dialing back to some very basic questions:
Who to market and sell to?
What to market and sell to them?
When to market and sell to them?
It may sound overly simplistic, but I'll get back to this in a moment.
My real awakening started with a dialog with a C-level client in a Fortune 100 company about 18 months back. We talked about the state of the business in the region this client managed. During this conversation, the executive drew the simplified segmentation model for the business on the whiteboard.
The top of the pyramid was Enterprise/Global which was about x-hundreds of accounts
The middle was Commercial I and II, about y-thousands of accounts
These two segments served as Named Accounts or Attended Accounts with a "feet on the street" sales coverage model. The rest were left to an inside sales team and channel partners. At the time, there was a big focus on the Commercial I and II segments, as there was a belief within the business that this represented the greatest growth area. To increase market share, the solution was more sales capacity with substantially more feet on the street.
This conversation troubled me because I had already started to dabble into account-centric data. I kept thinking that there had to be a more effective way to spend the total sales and marketing operating expenses (OPEX) to yield better business results. Furthermore, the buying process is very digital, and the actual sales engagement covers a small part of this buying process. I have been obsessed with this ever since. I have looked at different types of data to see if there is an optimal Go-to-Market (GTM) OPEX: first- and third-party intent. Install-base data and technographic data. I have looked at CRM data, opportunity data, Marketing Automation and advertising data.
My Eureka moment came a few months back, and the solution to all of this was right in front of me... in the same country, the same city, the same postal code, the same street, the same building: namely the Bisnode Group Analytics function lead by Rikard Candell. Within a few weeks, I learned how they approached the world using structured and unstructured (online) data, customer transaction data and machine learning (ML) to create highly valuable insights.
With the help of Rikard and his team at Bisnode, we are building out with one of my Fortune 150 clients a completely new data-driven perpetual model that will answer a few simple questions:
The last set of questions are key. Many leave it at 1-3, but I consider 4 crucial because the data-driven model is likely to create a big fishing pond. However, we want to fish with the right type of bait, the right fish e.g. audience, at the right time.
Over the next couple of months, Rikard and I will talk more about this with a client we will reveal at a later stage. This is by far the most exciting work I have been a part of in my career. Stay tuned!
" Analysing the customer base" may sound large and complex, particularly if "Artificial Intelligence" (AI) and "predictive analysis" are mentioned in the same sentence. Don't get lost in the tech and the buzz words, it doesn't have to be difficult. It's s