Which Cell Generates The Most Gross Margin Dollars?

We've learned several things in our case study this week, haven't we?

• Customers trained to enjoy discounts continue to enjoy discounts.
• Customers trained to pay full price continue to buy via full price.
• The customers who spend the most in the future pay mostly full price with "some" discounting.

So, which cell generates the most gross margin dollars on an annual basis?

The results are similar to the future demand/sales table.

• 1x Buyers?  51% to 75% on first order.
• 2x Buyers?  76% to 99% historically spent on items at/above their average price point.
• 3x Buyers?  76% to 99% historically spent on items at/above their average price point.
• 4x Buyers?  76% to 99% historically spent on items at/above their average price point.
• 5x Buyers?  76% to 99% historically spent on items at/above their average price point.
• 6x+ Buyers?  51% to 75% historically spent on items at/above their average price point.

In this case, you don't want customers who only pay full price. You want a mix ... but the mix needs to be heavily skewed toward items selling at/above their historical average.

Look at 1x buyers ... first-time buyers in the past year.  If they only bought discounted items, they generated $14.96 in gross margin in the next year.  If they spent 51% - 76% of their wallet on items selling at/above their historical price point, they generated $20.65 of gross margin dollars in the next year. 

Which customer would you prefer to acquire?

Most Valuable Customers by Price Designation?

Are the customers who buy items at a discount more likely to spend a lot in the future, or are customers who pay full price most likely to spend a lot in the future? Let's take a look at one example.

The answer? Neither!

In this example, as the customer becomes more loyal, the customer most likely to spend a lot in the future transitions from a customer who spent 76% - 99% on items at/above their historical average price point to a customer who, at 6+ life-to-date purchases, spent 51% - 75% on items at/above their historical average price point.

In other words, you want a customer who spends a mix of money (in this example) on items that are discounted and on items that sell at full price ... skewing toward full price early in the life cycle.

Tomorrow, we'll study which cells yield the most future gross margin dollars.

P.S.:  Look at the future sales numbers of customers acquired via 100% discounts (0% at/above the historical average price point). Just look at those numbers. Now go back to your customer acquisition strategy and ask yourself how much discounting you do, ok?

Training Your Customers How To Behave

Ok, here's a query for you. We take all customers and segment them based on life-to-date purchases. Then I select customers who place "average" average order values. Finally, I segment customers based on percentage of historical demand spent on items at/above the historical average price point of the item. Within the cells of the resultant query table, I measured the percentage of future (next 12 months) sales from items selling at/above their historical average.

Tell me what you observe.

The table illustrates key findings:

• Once you train a customer to bargain hunt, the customer bargain hunts.
• When you train a customer to pay full price, the customer is more likely to pay full price in the future.

Look at the customer who has bought 6+ times and has 26% to 50% of historical demand/sales coming from items selling at/above their historical average:

• 70.4% of future sales are from items at/above their historical average.

Look at the customer who has bought 6+ times and has 76% to 99% of historical demand/sales coming from items selling at/above their historical average:

• 82.4% of future sales are from items at/above their historical average.

Now, you may not think that a 12% difference in the metric matters.

It matters.

More tomorrow.

P.S.:  You create this table and have it as part of your dashboard, right?

Yeah, We Discount Online

The Executive says, and I paraphrase here:

• "It's almost like our customers don't want to shop from our catalog. We track orders we think were caused by the catalog, and even when we mail a catalog our customers seem to prefer shopping online without catalog attribution. I don't get it."

So, I dig into the information. Here's an interesting trend.

• Call Center Orders = $54.87 average price point, 29% of items sell below their historical average price point.
• Online Orders, Catalog Attributed = $47.03 average price point, 41% of items sell below their historical average price point.
• Online Orders, No Catalog Attribution = $45.25 average price point, 50% of items sell below their historical average price point.

I asked the Executive why this happens? Why do call center customers buy expensive items, while online non-catalog-attributed customers purchase items more than nine dollars cheaper, with half of the items selling below their average historical price point?

The Executive says, "yeah, we do a lot of discounting online".

And when you do that, you change customer behavior.

Those of you in the catalog world, folks who love to opine about the myriad benefits of an integrated omnichannel approach, well, you should think how integrated the approach is when you offer financial benefits to respond in one channel but not another.

Market Share and Profit

In my project work, there is a fundamental truth that is evidenced via the percentage of sales that are at/above historical averages, and the percentage of sales that are below historical averages.

• Market Share and Profit are at opposite ends of the strategic spectrum.

There are people in your company who misguidedly think that increasing sales from $88,000,000 to $97,000,000 causes you to increase market share and therefore, any profit you give up is worth it. Strong hint - increasing your market share from 0.04% to 0.06% is irrelevant.

Increasing profit is relevant. You can pay your ownership team, you can pay your executive team, you can pay all employees, you can reinvest the money in marketing, you can reinvest the money in capital expenditures. You have choices.

Do not be seduced by the co-worker who wants to increase market share. Market share is a game that Best Buy plays. It is a game not played by a brand selling widgets.

The Wrong Metrics

I frequently defer to sports, simply because the data required to understand sports is readily available. Hence, this is an interesting read ... a read about ranking the best college football teams from 2014.

I'm thoroughly convinced that, in e-commerce, we're analyzing the wrong stuff. Our fetish with conversion rates and ROAS is misguided.

So what if you executed a campaign with a 2.4% conversion rate and a 3x ROAS?

Our software tells us to optimize for campaign performance.

What if we optimized for business performance?

There is a major difference between campaign performance and business performance. One method seeks to optimize to help a brand win the week ending November 2. The other method seeks to optimize profit over five years.

Can you see the difference in strategy required to optimize conversions in a week vs. optimizing profit over a five year period of time?

Analytics Article

Read this (click here).

Now, think about your Google Analytics reporting or the dashboards you maintain/use or the vendor reporting that greatly overstates the performance of your efforts. Compare the reporting to what is discussed in the article. Do you see any parallels? You should see parallels.