I had a terrible experiance with a product (eggnog) from a brand I usually like (to be nameless)
TL;DR
- I give some functional defitions of GoodWill and Life Time Value
- Mitigate number of bad experiences and maximize good experience (who knew)
- If total lifetime spend exceeds life time value - they won’t buy anymore stuff from that brand.
- I will only be buying Darigold Eggnog for the foreseeable future
Background
To start, I’m going to give some background. Yesterday, I went to the store and purchased some eggnog from a brand that I usually buy other products from, but I’ve never bought eggnog from before (I deviated from the normal Darigold eggnog). I was very excited for it, then after trying it and having my wife try it, I was severely disappointed. And this is a premium brand and it tasted honestly terrible.
It got me thinking about a number of things: - How a brand shouldn’t diversify too much from the <<mentions>>22 immutable laws of marketing] - About how goodwill impacts the lifetime value of a consumer
We are going to be investigating this latter point. And this investigation will be taking place entirely from my armchair. I’m not even going to take the time to stand up, go to the bookshelf, and brush up on the current literature about Goodwill. So I may be repeating some points here that if you’re familiar with the literature are redundant.
For some quick definitions: - Goodwill is that ephemeral feeling that a consumer has about a product. - Lifetime value is how much a consumer will spend at a brand or a company for their “lifetime.”
Lifetime Value
Let’s start with lifetime value, LTV. We’re going to make an assumption that it is a function of Goodwill and some other stuff. We’ll refer to Goodwill as GW. The other stuff includes things like price and whatever else is of interest. For simplification, we’ll focus primarily on the price of whatever the product or the brand is being sold.
So we have something like this \[ LTV = \mathcal{f}(GW, p) \]
I’m going to make some other assumptions: - Goodwill is a value between 0 and 1 - LTV is an increasing function of goodwill and price So that’s our first-order conditions. FOCs will have a positive value for goodwill and price. So just to give it an actual formula: \[ LTV(GW,p) = GW * p * 100 \] This is basically to say the lifetime value of a customer with 100% goodwill is that they’ll buy the product 100 times. If goodwill is 50%, then they’ll only purchase the product 50 times. etc, etc. We could parameterize the 100, but I’m not going to do that right now.
Goodwill
Now let’s move along to Goodwill. Which is something that appears on companies’ balance sheet statements, especially when it comes to private equity and buying/selling of businesses. This is something that is pretty ephemeral and pretty hard to actually define, but we’re going to give it a whirl.
I would like to make the case that an individual’s good will for a particular brand will be based on the number of experiences they have with that brand and whether or not the experiences are good or bad. Nothing crazy. If you have more good experiences, then you have higher goodwill. If you have bad experiences, you have less goodwill. (Earlier, I said goodwill is bounded between 0 and 1. I think the case could be made that it is bounded between -1 and 1, or honestly, just unbounded. Goodwill can be negative - if you really dislike a brand - we’re not going to focus on that right now. )
All that to say, goodwill is a function of good experiences and bad experiences. And I think bad experiences should be weighted more heavily than good experiences. So here is our generic function, and an explicit form that I just threw together. We’re going to call good experiences ‘ge’, bad experiences ‘be’. \[ GW = \mathcal{f}(ge, be) \] \[ GW (ge,be) = \frac{ge - 5*be}{ge + be} \]
Forgive my folly; I’m not taking the time to properly bind goodwill between 0 and 1, but let’s just say that it is. What this form here tells us is that a good experience can be undone by 1/5th of a bad experience, and that in order to have 100% goodwill, you need to only provide good experiences with your product or service.
The five can be parameterized as well, and it represents the number of good experiences needed to offset a bad experience. In the example above, that would be five. Good experiences are needed to offset one bad experience.
Implementation
Let’s put it all together, and we’re going to plug in some actual numbers from what I feel like would be my life. First, we’ll calculate goodwill.
I’ve probably had about 13 good experiences with this brand and 2 bad experiences. The most recent one being this eggnog incident. So: \[ GW (13,2) = \frac{13 - 5*2}{13 + 2} = \frac{1}{5} \]
And we can calculate my lifetime value. The price for one of these products is, we’ll estimate, $10.
\[ LTV(1/5,10) = \frac{1}{5} * $10 * 100 = $200 \]
After this past experience, I will only want to spend $200 with this brand. We can take my total experiences, multiply it by the price, and get how much I have spent with this brand so far. We’ll call it Total Lifetime Spend, TLS.
\[ TLS(ge,be,p) = (ge+be)*p \] \[ TLS(13,2,$10) = (13+2)*$10 = $150 \]
My total lifetime spend has been $150, and my lifetime value will be $200.
Takeaway
If my total lifetime spend had been greater than my lifetime value, I would not have purchased from them again. But since it is not, I will probably purchase from this brand again. Definitely not eggnog, but I will probably purchase from them again, and they have an opportunity to increase my goodwill with future experiences.
For brands, it would be a good idea to understand how many good experiences it takes to offset one bad experience, and then incorporate that with your lifetime value of a consumer to see if you ‘still got them on the line’ and use it as a reminder to focus on quality.
Signing off, Best wishes
Gunnar J Newell