Loyalty Lizard Logic

I've measured this phenomenon more times than I care to mention.

"Brand X" is upset that customer loyalty isn't great ... so instead of doing the hard work to offer merchandise that customers have to have, "Brand X" decides that it must instead create a loyalty program, and then offer discounts/promotions and other nonsense in an effort to increase customer loyalty. The marketing analyst points out the following:

• 100,000 12-month buyers ... they spent $240 last year.

Then, an analyst mucks up the measurement process. She quickly determines the following:

• 10,000 12-month buyers are in the loyalty program / they spent $600 last year.
• 90,000 12-month buyers are not in the program / they spent $200 last year.
• Average customer spend last year = $240.

Powerpoint slides are quickly assembled ... and the analyst proudly proclaims that the loyalty program is creating customers who are worth 3x as much as non-loyalty customers. Everybody offers a round of applause ... they loyalty vendor, sitting in the room, winks at the CMO with an "I told you so" level of arrogance that makes the CFO want to vomit.

Why does the CFO want to vomit?

Because the CFO spent money on the loyalty program ... but still has a housefile of 100,000 customers spending $240 a year.

Nothing changed.

Well, two things changed.

• A loyalty vendor is getting paid.
• A marketing analyst is writing terribly biased queries.

But the organization doesn't care ... they put down the gas pedal. A year later, the results look something like this.

• 17,500 12-month buyers are in the loyalty program / they spent $580 last year.
• 82,500 12-month buyers are not in the program / they spent $170 last year.
• Average customer spend last year = $241.75.

Once again, everybody but the CFO misinterprets the data ... they see the $580 / $170 ratio, and they proudly proclaim that the loyalty program is causing a 3.41x increase in spend. #Wow.

But the CFO is doing slightly different math.

• 100,000 customers spending $241.75 = $24,175,000.
• 100,000 customers used to spend $240 = $24,000,000.
• Incremental value of the program = $24,175,000 - $24,000,000 = $175,000.
• Profit Factor = 40%.
• Cost of the Program = $100,000.
• Program Profit = $175,000 * 0.40 - $100,000 = ($30,000).

Technically, the CFO's math is also wrong. The CFO is assuming that all of the gain in 12-month buyer spend is attributed to the loyalty program, and that's not a fair assumption. More/less demand may have been generated, after accounting for changes in marketing strategy, discount/promo strategy, and merchandise productivity.

Regardless, you get the picture.

It is quite likely that the loyalty program actually caused Lifetime Value (LTV) to decrease, because the sales gain did not offset program costs.

And it is quite likely that the marketing executive will speak at a conference next year, and will tell the audience that they achieved a 3.41x increase in spend in their loyalty program. The audience will enthusiastically cheer, knowing that they've proven once again that loyalty programs work. They'll enthusiastically endorse lizard logic, won't they?

P.S.:  The marketing analyst and the CFO analyzed the data incorrectly. I could share how I'd analyze it, but you'd criticize me, suggesting I was measuring things incorrectly as well. Then, you'd share with me how you'd analyze the data, and I'd tell you that you were wrong. We'd all go in circles yelling at each other, all of us wrong. The key is to realize that as we triangulate toward an accurate answer, we all notice that sales are essentially not increasing, and that is the only metric that matters.

Romance Novels

Click on this little ditty ... and learn that 4% of print books are in the romance category, while 45% of e-books are in the romance category.

Our analytics are all messed up. We attribute the difference to channels.

The difference has nothing to do with the channel. The difference has everything to do with the content. In your case, study the merchandise that sells best in each channel. There are many times that low-margin, low price-point product sold via email discounts/promotions end up driving down lifetime value - has nothing to do with the channel, has everything to do with the product and promotion.


P.S.: If you like baseball, give this article about the Milwaukee Brewers trading away a bunch of current talent for what the GM calls "future talent" (click here). When your business is bad (similar to Milwaukee's record this year), do you plan for the future, or do you cut back on marketing expense to save money? Because if you do the latter, you reduce the future value of the business if your marketing cuts hurt customer acquisition activities.

But Their LTV Isn't Very Good!!

Who cares?

I ran into this one recently. The Marketing Executive held a report from a noted catalog boutique agency. The report suggested that customers acquired from "digital" sources were worth much less than customers acquired from "catalogs".

• Catalog Sourced Buyer = $50.00 Lifetime Value.
• Digital Sourced Buyer = $20.00 Lifetime Value.

The Marketing Executive said, earnestly ...

• "We don't want the Digital buyer ... they're worth less."

#OhBoy.

You know what this is?

Yup ... it's Lizard Logic!!

Old school catalog leaders are notorious for turning away "digital" buyers because LTV is not as good.

Who cares?

Do you think your CFO, if you told her that you could acquire 100,000 customers who would each generate $20 profit in the next five years, would say ... "nah, I don't want an additional $2,000,000 profit"?

Your CFO would flog you if you didn't generate $2,000,000 additional profit.

Here's the next line of reasoning I hear.

• "But the digital buyer doesn't like buying from the catalog, so that's a bad thing."

Who cares?

You know what? If the digital customer doesn't like buying from the catalog ... don't send the digital customer catalogs!!

Here's the next line of reasoning I hear:

• "But we are a catalog brand. It's our job to mail catalogs."

No.

You are a merchant. It is your job to sell things.

You want every dollar of profit you can find. Period. It is SO HARD to generate profit. Why would you turn profit away simply because the customer is worth less than another customer?

Impacting LTV

You just acquired a new customer. You lost money on the transaction (that's common).

You want your money back.

Which of the following two strategies is most likely to get your money back.

1. Market normally to the customer ... wait until the customer hasn't purchased in 18 months, then use vendor-centric reactivation strategies coupled with discounts and promotions to "win-back" the customer.
2. Immediately work hard to make sure the customer is happy with the first order, and encourage the customer to purchase for a second time within the first ten weeks following a first order?

The answer isn't even close.

It's (2).

Vendors push for (1) because that's how they make money.

You need to push for (2) because when the customer purchases for a second time (especially within 10 weeks), the customer is worth A LOT MORE than when you wait 18 months to convert the customer to a second purchase. You earn all of that incremental profit in the short-term, and, you push the customer to 3x or 4x or 5x status faster, so you earn even more profit in the long-term.

Any lifetime value simulation makes it perfectly clear that you have to do everything possible to get a customer to place a second order within 10 weeks of a first order.

What stops you from taking advantage of this fact?

What stops your call center from calling this customer to make sure the customer is happy? It's called a "call center", right? So call the customer!!

Ten weeks ... 70 days.

That's the window when you can make the biggest impact on LTV.

It's Fun To Acquire A Customer Via Discounts And Free Shipping!

It sure it!

But is it the right thing for your business? How does LTV vary between a customer earned the honest way (full price, no promotions) and a customer earned via cheating (discounts, promotions, free shipping)?

There are times when the customer earned via cheating is worth more, long-term.

There are times when the customer earned the honest way is worth more, long-term.

Your job is to do the math. No more theoretical arguments.

Let's run through a brief example. I typically create twelve-month profit value models for folks. The models might reveal the following:

Customer Earned The Honest Way.

• Probability of Purchasing, Next 12 Months = 40%.
• Amount of Net Sales Generated if Customer Purchases = $200.00.
• Gross Margin Percentage = 60%.
• 12 Month Ad Cost = $20.00.
• Pick/Pack/Ship Expense, as a % of Sales = 5%.
• 12 Month Profit = 0.40*$200.00*(0.60 - 0.05) - $20.00 = $24.00.

Customer Earned Via Cheating.

• Probability of Purchasing, Next 12 Months = 45% (better).
• Amount of Net Sales Generated if Customer Purchases = $215.00 (better).
• Gross Margin Percentage = 53% (worse due to discounts/promos).
• 12 Month Ad Cost = $20.00.
• Pick/Pack/Ship Expense, as a % of Sales = 10% (worse due to free shipping promos).
• 12 Month Profit = 0.45*$215.00*(0.53 - 0.10) - $20.00 = $21.60.

Well isn't that fun?!

• The discount/promo buyer is more loyal.
• The discount/promo buyer spends more.
• The discount/promo buyer generates less profit.

Now, as long as the brand is able to acquire 12% more customers via discounts/promos, then the math works out well ... you'll generate 11% less future profit per customer but you'll generate 12% more customers yielding more profit.

It is entirely possible that the discounts & promotions & free shipping are the right thing to do for your business.

But you have to do the math to know, don't you?

Are you running the math? Or are you being a "strategic marketer"?

Please ... run LTV math. I'm beggin' ya!

Just Show Me How To Calculate LTV

I know, I know, you just want simple math, something you can calculate on your own. 

Let's do something at a 30,000 foot level. Doing something at this level is better than the 90% of you who are not calculating LTV in any way, shape, or form.

Step 1:  Select any customer who purchased for the first time between 20100700 and 20110700.

Step 2:  Record the profit/loss generated by that customer on the first purchase. Don't have that data? Go get it. You wanted to do this yourself, so there are certain data elements you have to have. You'll have to speak with somebody in Finance. You'll have to speak with somebody in Marketing. You'll have to be proficient at calculating profit. You can do this!

Step 3:  In the next 12 months following the first order, please record the following data elements for each customer.

1. Total net sales generated.
2. Total gross margin dollars generated.
3. Total ad cost spent against this customer.
4. Margin Factor (percentage of margin that flows through to profit, independent of ad cost).

Step 4:  In months 13-24 following the first order, please record the following data elements for each customer.

1. Total net sales generated.
2. Total gross margin dollars generated.
3. Total ad cost spent against this customer.
4. Margin Factor (percentage of margin that flows through to profit, independent of ad cost).

Step 5:  In months 25-36 following the first order, please record the following data elements for each customer.

1. Total net sales generated.
2. Total gross margin dollars generated.
3. Total ad cost spent against this customer.
4. Margin Factor (percentage of margin that flows through to profit, independent of ad cost).

Step 6:  In months 37-48 following the first order, please record the following data elements for each customer.

1. Total net sales generated.
2. Total gross margin dollars generated.
3. Total ad cost spent against this customer.
4. Margin Factor (percentage of margin that flows through to profit, independent of ad cost).

Step 7:  In months 49-60 following the first order, please record the following data elements for each customer.

1. Total net sales generated.
2. Total gross margin dollars generated.
3. Total ad cost spent against this customer.
4. Margin Factor (percentage of margin that flows through to profit, independent of ad cost).

Now, this isn't going to get you to lifetime value, but it will get you to 5-year value, and that's a big deal.

Let's say that you have the following averages for Step 3, Step 4, Step 5, Step 6, and Step 7:

• Step 3 = $80.00 Sales, 50% Gross Margin, $20.00 Ad Cost, 10% Margin Factor.
• Step 4 = $60.00 Sales, 50% Gross Margin, $16.00 Ad Cost, 10% Margin Factor.
• Step 5 = $45.00 Sales, 50% Gross Margin, $12.00 Ad Cost, 10% Margin Factor.
• Step 6 = $35.00 Sales, 50% Gross Margin, $10.00 Ad Cost, 10% Margin Factor.
• Step 7 = $25.00 Sales, 50% Gross Margin, $8.00 Ad Cost, 10% Margin Factor.

For each step, we calculate annual profit.

• Step 3 = $80.00 * 0.50 - $20.00 - $80.00 * 0.50 * 0.10 = $16.00 profit.
• Step 4 = $60.00 * 0.50 - $16.00 - $60.00 * 0.50 * 0.10 = $11.00 profit.
• Step 5 = $45.00 * 0.50 - $12.00 - $45.00 * 0.50 * 0.10 = $8.25 profit.
• Step 6 = $35.00 * 0.50 - $10.00 - $35.00 * 0.50 * 0.10 = $5.75 profit.
• Step 7 = $25.00 * 0.50 - $8.00 - $25.00 * 0.50 * 0.10 = $3.25 profit.

Alright friends, we've got LTV:

• Year 1 = $16.00 profit.
• Year 2 = $11.00 profit, $27.00 cumm profit.
• Year 3 = $8.25 profit, $35.25 cumm profit.
• Year 4 = $5.75 profit, $41.00 cumm profit.
• Year 5 = $3.25 profit, $44.25 cumm profit.

At a high level, you have LTV at a cumm level for each of the first five years a customer is on your housefile.

Remember yesterday when we calculated payoff horizons? Apply that logic to your customer base after knowing how much profit you generate from a first order, and you've got everything you need to perform a 30,000 foot level LTV analysis ... remember, 90% of folks aren't calculating anything, so by following the simple steps here, you are well ahead of the curve. From here, you can follow your favorite University Professor and dig deep into advanced LTV theory.

But at least you'll be ahead of 90% of the competition.

That counts for something, right?

And you didn't have to pay a penny to obtain the information.

Payoff Horizon

Let's work through a very simple example.

Let's say that there are only two customers I can acquire each year.

• Each newly acquired customer generates $20.00 profit in year one, $12.00 profit in year two, and $8.00 profit in year three.
• Customer #1 can be acquired at a loss of $10.00.
• Customer #2 can be acquired at a loss of $25.00.

What should the strategy be for this company?

1. Do not acquire either customer, because the company loses money acquiring the customer?
2. Acquire only Customer #1, since Customer #1 is generated at a better profit rate than Customer #2?
3. Acquire both Customer #1 and Customer #2 each year?

This can be answered easily, by simply doing a bit of math. Let's run a three year scenario for each strategy.

If we do not acquire either customer, then here's what happens.

• Year 1 = $0.00 profit.
• Year 2 = $0.00 profit + $0.00 profit.
• Year 3 = $0.00 profit + $0.00 profit + $0.00 profit.
• Three Year Profit = $0.00.

Let's say for each of the next three years, we only acquire Customer #1 each year.

• Year 1 = -$10.00 + $20.00 = $10.00 profit.
• Year 2 = $12.00 (from year 1 customer) + (-$10.00 + $20.00) = $22.00 profit.
• Year 3 = $8.00 (from year 1 customer) + $12.00 (from year 2 customer) + (-$10.00 + $20.00) = $30.00 profit.
• Three Year Profit = $10.00 + $22.00 + $30.00 = $62.00.

Let's say that for each of the next three years, we acquire both Customer #1 and Customer #2. We already know the following for Customer #1:

• Year 1 = $10.00 profit.
• Year 2 = $22.00 profit.
• Year 3 = $30.00 profit.

So let's run the same scenario for Customer #2.

• Year 1 = -$25.00 + $20.00 = $5.00 loss.
• Year 2 = $12.00 (from year 1 customer) + (-$25.00 + $20.00) = $7.00 profit.
• Year 3 = $8.00 (from year 1 customer) + $12.00 (from year 2 customer) + (-$25.00 + $20.00) = $15.00 profit.
• Three Year Profit = -$5.00 + $7.00 + $15.00 = $17.00.

In total, then, the company that acquires both Customer #1 and Customer #2 generates the following:

• Year 1 = $5.00 profit.
• Year 2 = $29.00 profit.
• Year 3 = $47.00 profit.
• Three Year Profit = $5.00 + $29.00 + $47.00 = $71.00.

Which business do you wish to manage?

• Do Not Pursue Customer 1/2 = $0.00 + $0.00 + $0.00 = $0.00 three year profit.
• Pursue Only Customer #1 = $10.00 + $22.00 + $30.00 = $62.00 three year profit.
• Pursue Customer #1 + #2 = $5.00 + $29.00 + $47.00 = $71.00 three year profit.

If your goal is to never lose money acquiring customers, you go with the first strategy, and in three years, you have no incremental new profit.

If your goal is to maximize 12-month return on investment, then you go with the second strategy, and three years from now you have a customer file generating $30.00 of incremental profit, and for the three-year period, you generated $62.00 profit.

If your goal is to maximize the long-term health of your business, then you go with the third strategy, and three years from now you have a customer file generating $47.00 of incremental profit, and for the three-year period, you generated $71.00 profit.

THIS IS WHY YOU HAVE NO CHOICE BUT TO CALCULATE LIFETIME VALUE.

NO CHOICE.

Don't you think your Executive Team wants to have a discussion about whether they should pursue just Customer #1 or pursue both Customer #1 and Customer #2 each year?

Ever wonder why your business doesn't grow? Maybe you are not pursuing Customer #1 and you are not pursuing Customer #2.

Ever wonder why your business grows slowly? Maybe you are not pursuing Customer #2.

Ever wonder why profit as a percentage of sales is sluggish but total profit is good? Maybe you are pursuing both Customer #1 and Customer #2.

Show of hands ... 

1. How many of you calculate Lifetime Value?
2. How many of you know specifically which of the three strategies outlined above your business should execute to achieve company goals?

If you didn't raise your hand to #1, it's time to hire somebody like me, or hire your favorite vendor. There are many credible vendors who can help you measuring long-term value.

If you didn't raise your hand to #2, don't you think it is time to learn what your business will look like in the future based on different payoff horizons? Contact me now (kevinh@minethatdata.com) and let's get busy.

Lifetime Value Week

On Twitter, I get a lot of questions about lifetime value.

Lifetime Value, or "LTV" as some call it, is simply a measure of the future profit generated by a customer acquired today. There are 22,493 ways to calculate LTV ... so the point of this week isn't to teach you how to calculate LTV, though I will certainly share my thoughts about how I calculate it. Too many pundits, vendors, and analytical gurus will complain about any calculation style ... they're missing the point ... less than 10% of the companies I work with even bother to calculate LTV in the first place. Why have an argument about how to calculate LTV when almost everybody chooses not to calculate LTV?

Here's the interesting thing ... almost any statistical model created on an annual basis has LTV essentially built into it. Smart marketers who avoid all of the nonsense about individual campaigns tend to elevate the value of LTV to (at minimum) Marketing Leadership and Finance Leadership.

LTV requires the marketer/analyst to measure profit. Without profit, LTV has no meaning whatsoever. Who cares that a customer will spend $90 in the next twelve months if only 30% of sales flow-through to profit and the company will spend $30 in ad cost marketing to the customer?

Why was the last paragraph important?

• Profit = $90.00 * 0.30 - $30.00 = $27.00 - $30.00 = ($3.00).

See what I mean? That $90.00 LTV value is meaningless because it represents sales, not profit. Profit equates to a loss of $3.00. #OhBoy.

LTV, when measured in terms of variable profit (what some call "contribution" ... essentially it is profit prior to subtracting fixed costs), takes one of two trajectories.

1. LTV is low, and tends to drop off quickly when annual repurchase rates are low.
2. LTV is plentiful, and can actually increase over time if the customer has a 75% or greater annual repurchase rate and purchases 6+ times per year.

(1) is the reason that so many catalog brands are stuck and cannot grow. They cannot harvest enough long-term profit out of the customer (due to low annual repurchase rates and high ad-to-sales ratios) to overcome the steady decline in co-op response rates.

(2) is the reason that Wal-Mart, Amazon, Starbucks, McDonalds and many other "mega-brands" are what they are ... the customer purchases over and over and over and perpetually generates a mostly constant level of profit ... and this is what leads to the loyalty gurus claiming credit for their efforts (though their efforts have minimal impact on loyalty).

The worst companies spend to a cost-per-new-customer, independent of profit.

Good companies tend to calculate 12-month future profit for new customers, and invest in new customers to optimize twelve-month total profit among first-time buyers.

The best companies calculate future value for EVERY CUSTOMER in the database, regardless of where the customer is in the customer lifecycle. This allows the best companies to maximize future profit from EVERY CUSTOMER in the database.

More on this topic tomorrow.

Lifetime Value (LTV)

When I started working at Lands' End, back in the early 1990s, I was surprised how few companies calculated lifetime value.

When I work with companies in 2015, I am surprised how few companies calculate lifetime value.

#Sigh.

I know, I know, you don't have all the proper cost metrics and you use web analytics software that only allow you to evaluate campaigns and as a result you perceive that it is impossible to perform lifetime value analytics and you don't care anyway as long as your campaigns deliver an acceptable ad-to-sales ratio so so what?

All of the magic in your business comes from understanding how customers behave. No, not how they behave in campaigns ... but how they behave.

Do you have the table illustrated above? Do you review the table, at least quarterly? No? Why not?

The query is terribly simple.

• Identify all customers who purchased as of April 6, 2014.
• Segment those customers based on recency (three months increments) and life-to-date orders (1x, 2x, 3x, 4x-6x, 7x+).
• Then, for each segment, calculate the average amount of demand spent by the customer in the next twelve months.
• Produce the table outlined above.

How hard can that be?

And yet, there's a lot of value to be had from reviewing the table.

Notice how few high-value customers there are?

• 0-12 Month 7x+ Buyers.
• 0-6 Month 4x-6x Buyers.
• 0-3 Month 3x Buyers.

That's it.

Now look at all the low-value buyers (green and blue). Notice that a first-time buyer quickly moves into low-value status if the customer does not repurchase within six months. Don't you think that's something your whole company should know? Shouldn't every employee know that you have six months to convince a first-time buyer to purchase again, or the customer will descend into low-value status, requiring you to acquire another customer? Wouldn't your marketing team want to craft programs to convert the customer to a second purchase within that vital six-month period of time?

You don't have to perform a full lifetime value analysis to do the right thing. Just replicate the table above. It's not hard to replicate the table - the queries are terribly easy to replicate. Then identify the blue/green segments above, and do something to prevent customers from falling into the blue/green segments. By doing just this small amount of work, you replicate 80% of the value of a lifetime value program. Take the table above and convert it to profit, and you are 90% of the way there. And you've done virtually no work!

If you cannot produce the table, contact me (kevinh@minethatdata.com) and I'll do it for you.

A Great Predictive Metric: "Power"

You've probably heard about all of the geeky metrics that folks compute ... and you're probably saying "PRODUCE SOMETHING LESS NERDY, NOW!"

If you want something less geeky, something that tells you where your business is headed in the next year, calculate a metric called "Power".

Simply put, "Power" is the sales expected from your twelve-month buyer file in the next year.  Here's how you calculate it.

• Step 1:  Segment your 12-month buyer file however you wish.  We do this as of a year ago, say 2010.08.23.  Let's pretend that you have five segments ... A / B / C / D / F.  Let's pretend that you have 100,000 customers per segment.
• Step 2:  For each segment, calculate the average amount a customer in that segment spent from 2010.08.24 to 2011.08.23.  Let's pretend that As spent $100, Bs spent $50, Cs spent $30, Ds spent $20, and Fs spent $10.
• Step 3:  Count the number of customers in each segment as of today.  Let's pretend that today you have 80,000 As, 100,000 Bs, 120,000 Cs, 120,000 Ds, and 120,000 Fs.
• Step 4:  Multiply last year's value by this year's file counts, yielding file "Power"!

At this time last year, you had 500,000 customers who generated 100,000*100 + 100,000*50 + 100,000*30 + 100,000*20 + 100,000*10 = $21,000,000.  At this time last year, your twelve-month buyer file was capable of $2,100,000 of "Power".

As of today, you have 540,000 customers who are expected to generate 80,000*100 + 100,000*50 + 120,000* 30 + 120,000*20 + 120,000*10 = $20,200,000.  You have more customers, however, your customers aren't capable of generating as much "Power" as customers were capable of generating last year.

This is a particularly important concept for online / e-commerce folks, because your web analytics tools make it really hard for you to see how powerful your customer file is.

Best of all, this metric is predictive in nature, it doesn't tell you what happened in the past, it tells you what is likely to happen in the future.

Retailers tend to run this metric on a monthly basis (some weekly), so that they can understand key inflection points.

Power --- a metric you need to calculate!!

Value Grids and Lifetime Value

You probably already have something like this posted to your office/cubicle, right?

The "Value Grid" is a table that illustrates how much twelve-month profit you will generate from a customer with various Recency/Frequency attributes.

Freeze your file as of August 22, 2010.  Segment customers into Recency/Frequency combinations.  Then measure customer profitability across these segments, from August 23, 2010 to August 22, 2011.

Your benchmark is the Recency = 1 / Frequency = 1 segment.  This is how much profit you generate in the next year by acquiring a new customer.  If you lose $22.00 profit acquiring a customer, then you've got problems, because in this table, the customer pays back $6.52 in the next year.  Oh boy!

Similarly, you explore the cost to reactivate a customer against future payback.  If you have a 36 month 3x buyer with $2.43 future value, you might be willing to spend a few extra dollars to convert the customer to a 4x buyer.

Then look at the customers who pay the bills!  In this case, customers who purchased recently and purchased five or more times generate a boatload of profit, don't they? 

Create a Value Grid.  Post it on the wall of your office/cubicle.

Simple Tip: Customer Value By Day Of Week

Those of you who enjoy measuring long-term value might want to research customer behavior according to the day of week the customer purchases from your brand.

Retail customers purchasing on Saturday or Sunday have different future value than customers who purchase on a weekday afternoon or evening.

Online customers purchasing early in the week have different future value than customers who purchase evenings or weekends.

Catalog customers who buy during the in-home week have different future value than customers who buy two months after a catalog was mailed.

Those of you who analyze online visitation behavior will observe unique trends, based on the day/time the user visits your website.

Give it a try!

Lifetime Value And Return On Investment (LTV, ROI)

Multichannel CEOs and CMOs: How do you make decisions that shape the future of your business?

Recently, the best and brightest analytical minds (David, Jim, Ron) lamented the fact that Lifetime Value is not a widely accepted business concept. The concept was re-branded as "Return On Customer", with (at best) marginal corporate acceptance.

Loosely defined, lifetime value is the present value of future profits. Lifetime value frequently appears in two different ways. First, analytical folks focus on an analytical and financial approach to managing the business. Second, brand marketers focus on advocacy of customer rights as a way of increasing long-term shareholder value. If we could only get these two audiences to work together (analytics/finance and brand marketers), we might have something!

In many cases, Lifetime Value is discussed from an "outside-in" perspective. In other words, somebody outside a company (vendor, consultant) is trying to persuade somebody within an organization to purchase services, without knowledge of the real needs of the person "inside" a business. This can give LTV a bad name.

From an "inside-out" standpoint, many companies indirectly measure Lifetime Value.

• Catalogers are particularly good at measuring LTV, they manage list rental activities on the basis of LTV.
• In many cases, the Web Analytics folks don't have the software tools to do LTV measurement. Yet, they indirectly know this is important, because they like to measure the behavior of "new verses existing" visitors.
  
• Retailers often think of LTV in terms of "market share" or "most admired brand". Regardless whether this is flawed thinking or not, increased market share or being an admired brand deliver some of the benefits of a business with a customer base delivering outstanding LTV.

At some level, all companies and executives think about LTV. They just think about it differently than analytical folks, different than how the customer evangelist folks think about the problem.

Even better, let's get all the LTV evangelists together in a room, and let's see if they do things that are in the best interest of their own personal long-term health and financial benefit?

• We smoke, or drink alcohol, or overeat, all things that reduce our lifespan.
• We don't spend money in the best way. We purchase a Lexus or BMW or Mercedes that will depreciate from $60,000 to $0, when we could buy a Toyota Corolla. How does this decision help our own financial LTV?
• We pay via credit card, then pay interest. How does that help our financial LTV?
  
• We ignore health issues until they present dire consequences.

How can we expect "brands" to adopt LTV concepts when we don't take care of the LTV of our own financial or health concerns?

Like anything else in life, we know that LTV is good for us. All too often, we fail to follow through on what we know is good for us.

Based on my experiences working with business leaders, most would like to implement some version of LTV (they don't even know it is called LTV --- they just want a healthy long-term outlook that also generates lots of short-term profit). However, most Executives don't want the database marketing analyst hounding them about their thoughts and decisions.

• LTV is risk-averse. LTV might suggest that Apple focus on their core competency of making computers & software, might suggest they not invest in an unproven MP3 player that requires a significant capital investment.
  
• LTV tells you to invest in things that "work". Want to add new products to a catalog mailed to prospects? You can't, because new products probably don't have as good a LTV as existing products.
• Want to invest in a new creative representation of your "brand". You can't. LTV tells you that the existing creative is what is liked most by customers.
• Want to add a new catalog to your contact strategy? You can't, because LTV is telling you that you are over-saturating the mailing of your customers, lowering overall profitability.
• Want to add a third e-mail to the weekly contact strategy? You can't, because LTV tells you that too many customers opt-out after receiving more than two e-mail campaigns a week.
• Is your business in trouble, do you need to liquidate merchandise to open up your "open to buy"? Don't add a clearance catalog, because you'll lower the LTV of your full-price customers by converting them to full price + sale customers.

From time to time, LTV proponents struggle to see the business the way the Executive sees the business. Similarly, Executives make short-term decisions that mortgage or sub-optimize the long-term value of the business. Somewhere in-between these viewpoints represents the appropriate way to implement ROI-based decision-making within a business. That in-between place requires a culture that is willing to accept this thought process. Those cultures are hard to find.