Look at the bar chart below.
November 30, 2022
November 29, 2022
Some of the most enjoyable work I perform surrounds the life stage the customer is in.
In the bar chart below, we evaluate customers after a 1st / 2nd / 3rd / ... / 51st+ order. Within that order within the life stage, the chart evaluates the percentage of the amount spent that was on items selling below their historical average price point.
For this brand, what does the data suggest?
It suggests that the brand discounts heavily to best customers. Less than 25% of sales from first-time buyers is discounted ... after ten purchases, more than 40% of sales are discounted.
Every company has a personality - what the company believes in is revealed through the data sent to me. This company cares about loyal buyers.
November 28, 2022
Via Twitter user @popwreckoning, we are introduced to the concept of "Chicken Efficiency". This is one of the best stories I've read all year. Read the text in the image below to the end.
You'll hear about the amazing Cyber Monday that "brands" had all day today. Realize that research professionals, vendors, trade journalists, and pundits are measuring Chicken Efficiency.
You, however, are measuring profitability. Which is why you do not care about Cyber Monday.
November 27, 2022
Yeah, for one day they just gave some merch away in an effort to please, well, um, I have no idea who they were trying to please. By the way, if you average sales for the Monday before Cyber Monday and for the Monday after Cyber Monday, you learn (for this brand) that sales did not increase on Cyber Monday. Prices were lower, profit was lower, sales were identical.
November 24, 2022
Back to our table format studied this week. This time, each product / customer combination measures gross margin percentage.The green cells represent the highest gross margin percentages.
Do the best selling items have the highest gross margin percentages?
Do the best customers have the highest gross margin percentages?
If you think your best customers and your best products should yield the highest gross margin percentages, trust your instincts.
This business isn't being optimized properly.
Have you run this table for your brand?
The contact me (firstname.lastname@example.org) and let's get busy.
November 22, 2022
Back to the table framework we've been studying this week, take a look at share of sales from new items by product decile and customer decile.Two things are worth pointing out in this table. First, new items are seldom best-sellers. New items require patience ... they need to be developed (just like customers need to be developed). Second, there are interesting trends in the table. The best customers are less likely to buy new items than are other customers. We teach our best customers what they should purchase, and guess what? They purchase what we tell them to purchase!
The second point is an important one. If our merchandising/product teams want to sell something different, our best customers frequently say "no" ... the best customers hold back brands looking to change. This is why, so often, it is best to launch a whole new brand than it is to try to transform a brand from within. Best customers simply don't want to change.
November 21, 2022
I see this one a lot ... look at the New/Reactivated row, and compare the price these customers pay for merchandise compared to the best customers.Among the best selling items (the 5% column), best customers paid an average of $62.43 per item, whereas new/reactivated customers spent $71.96. This difference isn't as extreme through the remainder of columns, but the difference exists.
This happens A LOT in my project work. Either best customers are being given deals/discounts (whereas new/reactivated buyers are frequently given free shipping), or the merchandise preference is slightly different. Given that I'm controlling for the sales potential of the items in this table, it's a discounting issue.
Sometimes my clients wonder why it is so hard to acquire customers? Sometimes it's hard because you're asking new/reactivated buyers to pay 10% more per item than your loyal customer base is asked to pay.
November 20, 2022
I am in the process of finalizing a project package around discounts/promotions/pricing.
As is usually the case, I offer a significantly discounted project opportunity for loyal blog readers as I finalize the project code and test usability of the concept.
For you, that means I am offering two (2) readers the opportunity to purchase the discount/promo product (you've been reading about elements of what this project will become) for just $12,000 (it will be a $24,900 project when it is officially released).
Contact me immediately (email@example.com), because both spots will be gone shortly.
November 17, 2022
November 16, 2022
Ok, this isn't optimal because I'm not looking at gross margin dollars (that's reserved for clients), but you'll get the idea here about what I'm looking to accomplish.
I created regression models that predict the impact of prices on rebuy rates, and another model that predicts the impact of discounting on rebuy rates (again, gross margin work is done for clients).
The average price point for this category was $50.00, and the average percentage of items sold at/above the historical average price point was 75%. This yielded a 51.6% rebuy rate.
What happens if prices increase to $55.00 and discounting remains constant? Rebuy rates decrease to 49.7%.
What happens if prices increase to $55.00 and discounting increases so that just 56.3% of the items are selling at/above their historical average price point? Rebuy rates maintain at 51.5%.
This dynamic is coming to an omnichannel brand near you (your mileage will vary). Prices increased a year ago and continue to increase, customers balk at higher prices and purchase less often, leading "brands" to discount more to maintain response (which means that gross margin dollars decrease and the brand is less profitable).
It's hard to fight the customer. The customer is telling us how much s/he is willing to spend, and the customer does not care one bit, one bit, about how our cost-of-goods increased. Many of us are going to give up profitability, either by increasing prices / decreasing response, or by increasing prices / discounting (which decreases gross margin dollars).
November 15, 2022
The secret to discounting is to generate more gross margin dollars and build a stronger customer file (for some, it is to liquidate merchandise, but that is a topic for another day). The goal should never be to steal market share, because honestly you'd have to be a ten billion dollar brand (or larger) for that to even make the slightest difference.
So, if you choose to sell a $50 item with a $20 cost of goods for $35 via your promotional/discounting program, you must sell twice as many units to equalize gross margin erosion.
I worked with a smart brand who knew what this relationship looked like, and they discounted only enough to make the math work (or, in this case, come very close to working). In their case, I created regression models that predicted how much customers would spend next year on items selling at/above their historical average price point, how much customers would spend next year on items selling below their historical average price point, and how much gross margin dollars customers would generate next year.
For customers who spent $100 on items at/above their historical average price point and spent $0 on items below their historical average price point ...
- $64.41 spent next year on items at/above the historical average price point.
- $8.44 spent next year on items selling below their historical average price point.
- $73.05 spent next year, total.
- $45.37 gross margin dollars generated next year.
- 62.1% future gross margin.
For customers who spent $0 on items at/above their historical average price point and spent $100 on items below their historical average price point (discount-centric customers):
- $56.51 spent next year on items at/above the historical average price point.
- $28.74 spent next year on items selling below their historical average price point.
- $85.25 spent next year, total.
- $44.27 gross margin dollars generated next year.
- 51.9% future gross margin.
November 14, 2022
This example is from the pre-COVID era ... and the example didn't turn out the way I expected it to turn out.
When I looked at the percentage of sales at/above the historical average price point for an item by year of item introduction, I expected the brand to discount items more and more as the item aged. I didn't expect this:Some of the trends make sense to me. Newly introduced items (look at 2016 / 2017 / 2018) are more likely to sell at full price than are older items. This happens all the time ... older items are discontinued and are consequently discounted.
2019 looks different - you can see that this brand made a solid effort of re-establishing price integrity after several years of discounting.
As many of you are experiencing in 2022 ... when prices go up (either due to the end of discounting or because of cost of goods sold increases), response goes down. That's how this stuff works. Eventually, you land on a local maxima where pricing is theoretically optimized ... until it isn't once again.
November 13, 2022
This is from the pre-COVID era ... the before times ... I'm analyzing a brand that, over time, was becoming healthy. Look at the percentage of sales sold at/above historical average price points by year by pricing band (0 = lowest prices, 9 = highest prices).
When the company discounts, where does the company discount? With the lowest price points. The brand maintains price integrity on the most expensive items.
Compare 2019 to 2015. Tell me what you see?
Yeah, in 2015 this was a sick brand, selling half of merchandise at a discounted price. In 2019? Much healthier.
If you are a consultant like me, it's pretty easy to see when a brand is healthy or unhealthy, based on the prices that items are selling at over time. I realize that in 2022 many of you were forced to increase prices AND your business became unhealthy in the process ... that's a different issue than the one we're analyzing above.
November 10, 2022
This company doesn't do a lot of discounting, but they marginally prefer to offer discounts to the very best customers or the very worst customers. This signature comes up often in my work.
Again, the differences aren't huge (77% of items sold at/above their historical average price point for best/worst customers, 81% for middling customers).
But there are instances where you'll see 65% sold at/above historical average price point for an item among average customers and 25% sold at/above historical average price point for best/worst customers. Those situations don't end well ... you train the customer to wait for deals, and the "average" customer simply never purchases. Seen it a lot. No bueno.
November 09, 2022
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.
- 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.
November 08, 2022
November 07, 2022
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.
- 70.4% of future sales are from items at/above their historical average.
- 82.4% of future sales are from items at/above their historical average.
November 06, 2022
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."
- 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.
November 03, 2022
- Market Share and Profit are at opposite ends of the strategic spectrum.
November 02, 2022
November 01, 2022
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.
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