Parsing Through Channels - Incremental Impact of One Channel

You have a segment of customers. Based on your best guess for attribution, here's how the customer segment behaves.

• 40% Annual Repurchase Rate.
• Half of demand is organic - not caused by marketing.
• 25% of demand is caused by email marketing.
• 10% of demand is caused by social.
• 10% of demand is caused by search.
• 5% of demand is caused by other marketing activities.

Look at email marketing. 25% of the 40% repurchase rate (10%) is caused by email marketing. If you improve email marketing productivity by 15% by featuring better merchandise, you impact rebuy rates by 10% * 15% = 1.5% ... a 40% repurchase rate becomes a 41.5% repurchase rate.

That may not seem like much to you. But follow these assumptions.

• Base Case Profit = 40% Rebuy Rate * $150 per Repurchaser * 40% Profit Flow-Through - $10 Customer Ad Spend per Year = $14.00 Profit.
• New Case Profit = 41.5% Rebuy Rate * $150 per Repurchaser * 40% Profit Flow-Through - $10 Customer Ad Spend per Year = $14.90 Profit.

Multiply that out across your email subscriber base and you have something. In Marketing Budget Experiments, you get to see how this becomes compound interest over time ... which is kinda cool to be honest!

Budget Adjustment

Here's a subtlety you likely deal with.

Assume a segment of customers had 10,000 buyers last year. This year the segment has 12,000 buyers.

Let's pretend that you are holding your retargeting budget constant this year ... you are essentially spending the same amount year-over-year at a segment level. Now, I realize you are not executing retargeting at a segment level, you execute it at a budget level. But your budget-level decisions impact segment-level performance.

Pretend that the segment of customers above has a 40% annual repurchase rate. Pretend that retargeting accounts for 10% of the 40% annual repurchase rate ... 4%.

Because you are spending the same amount but have 12,000 customers instead of 10,000 customers, your repurchase impact is (10,000/12,000)*0.04 + 0.36 = 0.833*0.04 + 0.36 = 0.0332 + 0.36 = 39.3%.

Stated differently, when the customer file grows but the budget remains constant, rebuy rates decline. Not a lot (in this example) ... but something to think about.

Payback Window

When focusing on Marketing Budget Experiments, there is a tension that must be resolved.

The tension? How much time needs to pass to optimize profit? And ... when is profit optimized?

These are not easy questions to answer.

The company below spends $100,000 acquiring customers ... then the newly acquired customers pay the brand back. In the Marketing Budget Experiment below, we simulate what happens at different customer acquisition investment levels. Each row represents cumulative profit after "x" years. Click on the image - the numbers are tiny but are important.

If you want acquisition efforts to be optimized? Spend $25,000.

If you want your payback window (in this example - your mileage will vary) to be optimized after one year?  Spend $50,000.

If you want your payback window to be optimized after two years? Spend $75,000.

If you want your payback window to be optimized after five years? Spend $125,000.

If you want your payback window to be optimized after ten years? Spend $175,000.

None of the scenarios require the brand to spend what the brand is currently spending ... $100,000.

All of the scenarios give you something to think about. Everybody will have an "opinion" about what should be done, about what is "right". Not many people will agree.

Be honest with yourself. What decision would you make here? Explain your decision.

Do you have an application that performs this level of insight for you?

How Winners Impact Marketing Productivity

Ok peeps, we have our relationship.

Let's take a brief trip in the way back machine. It's 1993. I'm sitting in a conference room at Lands' End. We have all of our spreads from a catalog on the wall - each spread has a tag board color that represents how profitable the spread was. Now, we did this for all of our monthly catalogs, and over time we realized that if we populated the first twenty pages of the catalog with our absolute best sellers (called "winners"), the catalog outperformed catalogs where we dumped garbage in the first twenty pages. This fact applied in two different ways. First, you needed the best merchandise. Second, you needed the best creative. I recall one item which was re-shot with an employee instead of a model - and that item dropped in productivity by 30% while comparable items with model-centric creative performed on plan. So you needed the best products and the best creative. If you did both, the catalog "worked better", and as a result you could mail the catalog to more customers/prospects, which caused more customers which caused future catalogs to generate more sales.

Yeah ... a lotta "more" going on there.

That was 1993. It's 2023. Ask your e-commerce executive if she is featuring the best selling items with the best creative where possible? Too often, the answer is "no", and you'll get a flimsy answer in response to your question ... something about "defending the brand".

Even a five percent increase in productivity makes a difference. Here's an example.

Here a marginal five percent increase in productivity (due to featuring winning items and winning creative - not hard to do) turns a money-loser into a profitable endeavor. The incremental sales (in this case, your mileage will vary) are generated at a 54% variable operating profit (contribution) rate. Your CFO likes those situations.

Now that you are making more profit, you can spend more money to get near break-even.

You can spend an additional $4,000 ... 4% more ... because productivity is 5% better ... and you still end up making more profit.

If you work hard on Category Development, your marketing productivity improves. If your marketing productivity improves, you can spend more marketing dollars ... sales increase ... profit increases ... and you have more customers to market to next year.

Sounds like a good thing, right?

The Organic Percentage

Back to our relationship.

One of the most fascinating aspects of marketing is understanding what your Organic Percentage is.

The Organic Percentage is, of course, the percentage of customers/sales that happen if you do nothing. If you don't spend any marketing dollars in a given month, you will still get new customers.

If you are a startup, your Organic Percentage is low. Nobody knows who you are, and you have to do "something" to create awareness.

If you are Macy's, everybody knows who you are and many have forgotten you altogether! Regardless, you spent decades "building a brand" ... and that brand pays you back via new customers who shop without the aid of marketing spend. Purists would suggest that marketing dollars spent in 2006 are paying off in 2023, and they are probably right ... but you don't "know" that so you cannot attribute Organic New Customers today to marketing activities in 2006.

What happens if you don't know your Organic Percentage?

What usually happens is this ... if you are trying to figure out how much to spend in a month, you'll fit a line that is more linear in nature, causing you to think you can spend more marketing dollars monthly when in reality you simply can't do that.

Know your Organic Percentage, ok? Please, know this metric and thoroughly understand it!

The Curve

Here is our image from yesterday.

The key to any Marketing Budget Simulation (this topic is being explored and will come together as we work through our examples) is to understand the law of diminishing returns. The law is apparent in the image above. The red line depicts this relationship.

• 900 new customers on $0 spent.
• 2,385 new customers on $50,000 spent.
• 3,000 new customers on $100,000 spent.
• 3,472 new customers on $150,000 spent.
• 3,870 new customers on $200,000 spent.

If you spend nothing, you still get 900 new customers. This is an important finding, one we'll talk about tomorrow.

If you spend $50,000, you get 2,385 - 900 = 1,485 new customers.

If you spend an additional $50,000, you get 3,000 - 2,385 = 615 new customers.

If you spend an additional $50,000, you get 3,472 - 3,000 = 472 new customers.

If you spend an additional $50,000, you get 3,870 - 3,472 = 398 new customers.

This is the law of diminishing returns. You spend more, you get less.

This law dominates marketing spend. Sometimes this relationship is absolutely punitive, sometimes it is nearly linear (suggesting that the brand could spend a lot on marketing and not be penalized).

This curve, this "law of diminishing returns" dictates everything we do. It's the reason we cannot spend a ton of money. You see the results via ROAS ... old school marketers see it via the ad-to-sales ratio (which is the inverse of ROAS). Eventually your tactics simply no longer work.

This curve, interestingly, can be used to simulate the relationship between short-term profit and long-term profit (i.e. CLV or LTV or whatever you want to call long-term value). If you know how much a customer delivers in the future and you know the relationship above, you can find the place where your business is healthiest over time.

And if you manage your categories appropriately, you lift these curves, allowing you to spend more.

A Beautiful Relationship

This image is going to provide the foundation for what I will talk about during the remainder of April (and possibly beyond). So yeah, it's an important image and you should click on it, print it, and post it in your virtual office or your corporate office. Here we go.

In this graph, I am depicting multiple topics simultaneously. The core relationship being shared here is one between monthly ad spend (x-axis) attributed to new customers and monthly new customers (y-axis).

The three lines depict different curves observed in my project work. Sometimes (green) you can keep spending ad dollars and keep getting new customers. Sometimes (blue) you spend and get a lot of new customers, then the well runs dry.

The arrow represents the organic percentage ... the percentage of new customers you generate if you don't perform any advertising at all.

Tomorrow we'll start diving into some of the topics associated with this image. When we think about Category Development and how it relates to what is coming, we're thinking about ways to boost the trajectory from a Sharp Trajectory (not good) to a High Trajectory (good).