Our members are leaving and the franchisees are complaining. What can we do fast to make a difference?
Introducing the Seven Rules of No Excuses Marketing
Part 1 of 2
Our client was in a jam. Customers were declining, which meant that attrition was exceeding acquisition. The major franchisees had begun to complain, and of course they made it into Corporate’s problem (don’t they always?). In order for our client, the VP of Marketing, to maintain his credibility (and perhaps his job), we needed to get some insight, quick.
This was not the time for complex modeling projects that could last for months; rather, it was time for a rapid analysis and solution development that would make a difference “in real-time.”
This week, I spent time working with a client who had limited budget (who doesn’t?) and limited time (the same thing). He found himself between a rock and a hard place, because his franchisees didn’t always enter their data correctly, but he was on the line to give them a data-driven solution to address an increasing attrition problem. Since his data wasn’t clean, he met resistance when he asked the IT team to help out with his analysis. If he couldn’t understand the problem, he couldn’t develop a solution. Time was running out, and the CEO wanted an update in a week’s time. What could he do?
Using the No Excuses Marketing approach, we worked together to understand the problem in a week and develop a solution to began to address the attrition problem in less than 90 days. Here is how we did it:
No Excuses Marketing Rule #1 — “Don’t complain about what you don’t have; use what you got.”
Too often, I have been in discussions with Marketers that overly focus on the limitations of their current situation — too much to do, not enough headcount, slashed budgets, etc. These marketers get lost down the rathole and fail to see the opportunity in front of them: never before in history have so many resources been available to the resourceful for so little, so fast. The key to to understand what you have and what you can do with it, using down and dirty approaches to driving ROI F-A-S-T.
Quickly we figured out that about 70% of his data was accurate, and that for his best franchisees, the data was close to 90% accurate. It was easy to get caught up in the inaccuracies
- Some customer IDs were reused, making it look like he had more customers than he actually did.
- Additional services for those customers were only accurate for about 20% of franchise locations
- Some customers had been suspended and then reactivated on the same day due to bad billing practices, and so on
It is easy to look at his data and conclude that it is just a pile of mess, and that we could not tell anything for certain. That conclusion would be exactly 50% right. The data was a pile of mess — that was true. Any while we could not tell anything FOR CERTAIN (100% accurate), we could see trends and patterns in the data from the 70% of franchises where the data was good-to-great quality. Remember, the problem was attrition at the customer level — we did not need to analyze every customer to see the patterns, only some of them. So while the answer was not 100% accurate, it was more than accurate enough for…
No Excuses Marketing Rule #2 — “Data only has to be accurate enough for the decision that needs to be made.“
Marketers often hesitate to conduct analysis, make conclusions and act based on data that is less than complete. The truth of the matter is that data is always incomplete, even when it is portrayed as perfect. The tendency is to wait and wait and wait, until data entry is more accurate, until the data warehouse is built, and so on. The key word is “wait.” During that waiting time, the business loses substantial incremental revenue and relationship opportunities based on the data that is available. Remember, if you have data that is 70% complete, you can act on it better than you can act with no data at all.
We identified the franchisees that the company believed had the best data practices over the past year. Then we checked the data to see if those franchisees actually did have clean data. In general, those franchisees had better than 90% complete information. We isolated the data from those franchises and then looked at available customer information — average number of visits, services purchased, time since last visit, distance from home to franchise, etc., comparing each factor for customers who attrited (canceled their memberships) compared to those who were retained.
This analysis is a classic example of the another rule of No Excuses Marketing…
No Excuses Marketing Rule #3 — “Make your spreadsheets work hard to make your project run fast.”
An exact answer is often the enemy of getting things done. Key trends in the data can often be identified using spreadsheets and some experience on typical drivers of customer behavior across categories. You can also brainstorm other factors and check them out for validity and impact. But this sort of work can be done in 2-3 days time, rather than the weeks it might take to build, test and tune predictive models. I am not knocking predictive analytics at all; rather, they function best when the opportunity is large, the patterns unclear and the timing longer. When the heat is on, spreadsheet analysis will get you started on earning ROI fast.
How did this client take numbers on a spreadsheet and turn them into profits in the bank? Stay tuned to our next episode…
