Reminder: The MineThatData Elite Program

Here's a quick reminder for those of you looking to participate.

In this run of the MineThatData Elite Program, we'll cover the usual metrics that evaluate the success of your customer file. But I'll also add one feature. I'm going to measure the Customer Development of the customers you acquired last April, at the start of the pandemic. We'll see how these customers evolved and changed over time. We'll see if you did a good job of developing the customers blessed to you during an awful pandemic.

Cost? $1,000 for existing subscribers. $1,800 for first-time subscribers. Participation is 100% voluntary.

Contact me for participation and file formats (kevinh@minethatdata.com)

Due dates? Five years of data (one row per purchase transaction) delivered in .csv format. Data due by February 15, 2021. Payment due by February 15, 2021. Analysis delivered by February 28, 2021. 

Tell Me Where In The Customer Development Process These Ads Belong?

Tell me your thoughts?

Both Headphones.com and Belardi Wong ads came from anything other than purchase intent. Headphones.com was part of a research process. Belardi Wong happened because a colleague wanted to know who to hire for a specific task, so I sent an email to the person with the link in the email. That information got sniffed somehow and now Belardi Wong is advertising to me. On a soccer "table" page. And if Direct Mail delivers the best customers, why are they advertising digitally? Wouldn't a direct mail campaign, directly to my mailbox, make the most sense? Yes, I'm kidding here ... but I'm asking you to think.

Think carefully about where in the Customer Development process the Belardi Wong ad falls, given what you know about my intentions?

Customer Development is about having a plan ... knowing where prospects and customers are in the life cycle, knowing how fast the customer is degrading in value, and then aligning marketing tactics by degredation levels. If your favorite vendor violates Customer Development principles, talk to your favorite vendor about it.

Customer Development Over Time

Alright, in this case we're evaluating customers acquired in the month of June. We're going to spend several days following these customers over the course of a year, so that you can see how customers develop and change over time.

The first image (below) shows how customers evolve and change in the very first month the customer was acquired (June).

In the acquisition month, 4.5% of the customers have already purchased for a second time! In fact, some of the customers have already purchased three times.

In the next month, customers could repurchase. If they repurchase, they move up to the Recency = 1 Month row. If they don't repurchase, the fall down to the Recency = 2 Months row.

Keep an eye on Recency = 1 Month row over time ... these customers keep buying, and as time progresses more customers move into frequency = 2/3/4 segments (called "Emerging Customers"). After the first full month on the file, 7.7% of customers have purchased for a second time.

On to August.

By the end of August, 9.7% of customers purchased for at least a second time, with the vast majority having purchased for a second time ... by this time 1.2% of customers purchased for a third time and 0.3% have purchased for a fourth time (even a tiny fraction of customers have purchased a fifth time, or a 6th-10th time).

At the end of September?

Well, the Welcome period is over, so first-time buyers are now classified as "Retiring" because their repurchase probability is progressively worse from here on out. 12.6% of customers have repurchased. Only 0.3% of customers have achieved Loyal status through three months.

Do you see how hard it is to get customers to Loyal status?

It's really, really hard.

At the end of October?

Repurchase Rate is up to 15.7%.

12.1% of the customers are 2x buyers.

2.4% of the customers are 3x buyers.

0.6% of the customers are 4x buyers.

0.2% of the customers are 5x buyers.

0.3% of the customers purchased 6+ times.

After four-and-a-half months customers are still generally in the 1x/2x stage. Few customers have moved into the high levels of Emergence, and only 0.6% of the customers are now Loyal.

This is why it is so darn critical to have a Welcome program. If the customer doesn't get out of the Welcome stage and migrate into Emergence quickly, you can't get the customer over the hurdle into Loyal status.

Emergence at the 12 Month Timeframe

Did you notice the rows I highlighted in the table from a few days ago?

The top four rows are colored red - those are the timeframes when the customer is most responsive.

Now notice what happens at Month = 11 and Month = 12. When the customer lapses to 11/12 months, the customer (in this example) becomes marginally more responsive.

This is a common outcome in my project work. Many brands have customers who like to buy during "Anniversary" events, be it every Christmas, or on Valentine's Day or Easter or they buy gardening products in Spring. Regardless, there is Anniversary behavior that accelerates repurchase behavior.

So the customer briefly "unretires" and becomes active, before settling back into Retirement mode.

In Customer Development, we always pay attention to customers at recency values of 11/12 months since a last purchase. This is a time to reach out and give these customers a reason to buy something, because they are marginally more likely to purchase again. It's an opportunity to move the customer back into an Emergence stage.

It's Time! The February Run of the MineThatData Elite Program

Four months go by quickly, doesn't it?

In this run of the MineThatData Elite Program, we'll cover the usual metrics that evaluate the success of your customer file. But I'll also add one feature. I'm going to measure the Customer Development of the customers you acquired last April, at the start of the pandemic. We'll see how these customers evolved and changed over time. We'll see if you did a good job of developing the customers blessed to you during an awful pandemic.

Cost? $1,000 for existing subscribers. $1,800 for first-time subscribers. Participation is 100% voluntary.

Contact me for participation and file formats (kevinh@minethatdata.com).

Due dates? Five years of data (one row per purchase transaction) delivered in .csv format. Data due by February 15, 2021. Payment due by February 15, 2021. Analysis delivered by February 28, 2021.

The Customer Emerges

Last week we talked about the attributes that customers possess after a first order. Those attributes separate customers who are unlikely to purchase a second time to customers who are more likely to purchase for a second time

When the customer purchases for the second time, the potential of the customer Emerges. In other words, you use print and email marketing and website personalization to give your first-time buyers the best chance to purchase for a second time ... you Welcome the customers and treat them the best way you can to facilitate a second purchase.

With each additional purchase, the customer becomes more likely to purchase again. The process begins to accelerate, and your role in Developing the customer changes. 

Here are the results of what is called a "Life Table". In the table, we look at conditional probabilities of buying again based on where the customer is in the life cycle (frequency - across the top of the table) and recency (months since last purchase ... the rows of the table).

Click on the table to get a better view of the information. I want you to look at the "1x to 2x" and "2x to 3x" columns in the table under the "Incremental Rebuy Rates" column.

Let's read down the "1x to 2x" column first. When we acquire a customer, the customer moves into the Welcome stage. In the acquisition month, the customer has a 4.5% chance of buying again. If the customer does not repurchase that month, the customer degrades down to a recency of one month, where the customer has a 7.0% chance of buying again. If the customer does not repurchase that month, the customer degrades down to a recency of two months, where the customer has a 3.0% chance of buying again. The customer is beginning the process of Retirement (even though the customer just bought for the first time). You are losing the customer.

However, if you get the customer to purchase for a second time, the customer begins to Emerge ... the customer has Potential. Read down the "2x to 3x" column.

• 7.7% chance of buying for a third time in the 2nd purchase month.
• 16.7% chance of buying for a third time if the customer lapses to Recency = 1 month.
• 5.2% chance of buying for a third time if the customer lapses to Recency = 2 months.
• 4.0% chance of buying for a fourth time if the customer lapses to Recency = 3 months.

The "Retirement" process is mirrored here, but the incremental repurchase rates are higher.

Now look at cumulative repurchase rates.

• 1x to 2x through three months = 15.6%. 1x to 2x through twelve months = 24.7%.
• 2x to 3x through three months = 30.0%. 2x to 3x through twelve months = 43.9%.

If you get the customer to a second purchase, the customer begins to Emerge ... the customer is beginning the journey to becoming a loyal buyer.

And if you can push the customer from a 2nd purchase to a third purchase, the story gets even better as you watch the customer migrate from a third purchase to a fourth purchase.

• 1x to 2x through three months = 15.6%. 1x to 2x through twelve months = 24.7%.
• 2x to 3x through three months = 30.0%. 2x to 3x through twelve months = 43.9%.
• 3x to 4x through three months = 44.9%. 3x to 4x through twelve months = 58.8%.

Finally, the customer can be pushed from a 4th purchase to a 5th purchase, and that's where the customer is cemented in Loyal status.

• 1x to 2x through three months = 15.6%. 1x to 2x through twelve months = 24.7%.
• 2x to 3x through three months = 30.0%. 2x to 3x through twelve months = 43.9%.
• 3x to 4x through three months = 44.9%. 3x to 4x through twelve months = 58.8%.
• 4x to 5x through three months = 59.7%. 4x to 5x through twelve months = 71.8%.

You've got it ... the customer is now Loyal!!

The process of going through a 2nd/3rd/4th purchase stage is called "Emergence". You "Welcome" a customer and encourage a second purchase ... then you do the hard work of pushing the customer through the Emergence stage into Loyalty. Each step in the process you are rewarded, because the customer becomes more and more likely to buy again.

It almost seems like we're going to need a Customer Development Score (CDS) to manage this process, doesn't it? I'll bet this series ultimately takes us to a Customer Development Score.

31 - 26

My Packers were trailing 31-23 late in the 4th quarter to Tom Brady and the Tampa Bay Buccaneer. In spite of playing poorly, the team rallied, forcing Mr. Brady to throw three (3) second-half interceptions. Three! In a half! But here they were, with first and goal. Then second and goal. Then third and goal. And finally, it was fourth and goal. At the nine yard line.

The Packers just blew three scoring chances.

If the Packers went for it, several things would have to happen in succession for the Packers to win.

They'd have to convert fourth and goal ... maybe a 1 in 5 chance. Then they'd have to convert the two point conversion, a 50/50 proposition. Then they'd have to stop Tom Brady from scoring in the final two minutes with a full compliment of time outs. Good luck there! And if that happened, they'd have a 50/50 chance of winning in overtime. If they didn't get a touchdown on fourth and goal, they'd have to stop Tom Brady on three downs, use timeouts, then get the ball back and go all the way down the field and score and get a two point conversion just to get to overtime where they'd have a 50/50 chance of winning.

In other words, the math wasn't great if they went for it on fourth down.

So Green Bay kicked a field goal. Down 31-26, they needed to hold Tampa Bay, use their timeouts, get the ball back, and then they had to score a touchdown ... but the difference was if they scored a touchdown they'd win the game ... no overtime.

In other words, there were two lousy choices, each unlikely to succeed.

Green Bay kicked the field goal, and trailed 31-26.

They weren't able to stop Tom Brady and the Bucs. Final score, 31-26.

That's where football Twitter lost their ever-loving mind.

"Worst call ever". "Why did they do something so stupid??".

The advanced analytics folks "did the math" and suggested that Green Bay had a 27% chance of winning by kicking the field goal, and a 25% chance of winning by going for it. Both choices were bad. But one choice followed conventional wisdom (go for it), and the other choice marginally improved the odds of winning but looked like a bad choice (kick the field goal).

This situation happens in business all the time. You are faced with a choice ... conventional wisdom, or something new and somewhat unproven?

It's safe to follow conventional wisdom ... nobody is going to criticize you for making a decision that everybody else would make. Even if your odds of generating profit are lower, you're still doing what everybody else would do. Everybody is happy with your decision.

But did you make the right decision?

Let me give you an example. What month is it easiest for most of you to acquire new customers? It's December (or very late November), isn't it? For some of you it is November. If you are a gardening brand, it might be in April. So conventional wisdom tells you to acquire a new customer "when the fish are biting". Nobody is going to criticize you for spending money on Cyber Monday.

Now, the data shows something different. When I run my simulations, I easily see that the best time to acquire a customer is 1-3 months prior to your peak season. If you acquire a customer in October, for instance, the customer is hyper-responsive in November/December during your peak season. This means you "Develop" more customers who will pay you back the next year. You earn more future profit by "Developing" customers, and that profit offsets the money you lose acquiring the customer in a non-peak window.

So what do you do? Do you follow conventional wisdom and stuff more money into Christmas, or do you do something that is unpopular but generates more profit for your company over time? 

I know what I'd do.