Analytics: science or art?
It is both.
Marketing analytics has not been a focus for marketing teams for a long time, and when done, it was mainly for graphic presentation and results that would not drive action for further planning. Nowadays, it is considered one of the most important, and it should a reality for your startup.
The main reason for using analysis is to understand what happened in the past, give you better control of what is happening now, and for me, the best part, help you to predict what might happen in the future – and if your prediction result is not the best at least you’re able to visualize it; that’s when the art arises; based on your data analysis, you have the chance to act now and change the course of your future.
It is common to think about marketing analytics in the digital world when we know that almost all companies work with advertising; however, marketing analytics go way beyond that. We’ve talked a lot about how B2B marketing and sales are complex, and this is an exciting topic to recognize at least one process we might benefit from compared to B2C companies. Most B2C methods are not as simple as selling directly to the customer; other flow components generate lots of different data. To understand how complex marketing analytics can be, let’s start by understanding the 3 types of data:
Manufacturer data:
Refers to all shipment and billed data coming from the company’s product.
Intermediate data:
Depletions or replenishment data come from the wholesalers and distributors.
Retailer data:
Finally, the point-of-sale data – the direct contact between retailers and consumers.
In my town, there was a grocery called Montelibano. I used to go there after school to buy a coke. Montelibano does not produce coke, and Montelibano does not buy coke directly from Coca-Cola. Based on this, how does Coca-Cola know what’s going on with their customers?
This is the type of problem we, as B2B startups, usually won’t have to worry about. If you’re wondering how to apply the types of data to B2B, mainly SaaS, it is way simpler! In our case, we just have 1 type, the manufacturer data.
Considering we have all the data of our customer flow, it means we have more control of what is going on, and a higher probability of having more accurate results, which might positively affect sales forecast and price changes.
Analytics is the key to making the right decisions, and if not applied daily, it might ruin your business, even if it is a B2B Startup. Recently, I had to plan the OKRs for my marketing team, and one of the questions that I had was:
“I have these 2 products to run ads for, last quarter we generated 50 leads, 12 for Product A and 38 for B. Which one should I focus on more?”.
While analyzing my numbers, the CEO asked:
“What’s the quality of the leads generated for each product?”
When I opened the qualitative data, we saw that most of the 12 leads for Product A were not qualified; while compared to the 38 for Product B, the sales opportunities generated were higher; in reality, the leads for product A were general Gmail accounts that never replied to sales while the other had emails with relevant domains and we indeed received a lot of good responses that turned out to be sales demos.
As a marketer, I was thrilled with the number of leads generated and I honestly thought both of them were running well. Although the leads for Product A were not generating real sales opportunities. I was only able to proceed with my OKRs after analyzing the quantitative and qualitative data for the previous quarter, as well as adjusting my budget and full product campaign strategy.
Now, I have my MQL number, my budget the adjustments for the LinkedIn campaigns, and a CEO happy and confident that what we planned is realistic and achievable.