Your first hundred buyers already told you what to build next
You own the research already. Read purchase history and lifetime value to choose product two, instead of picking from a list of ideas in your notes app.
There is a note on your phone with eleven product ideas in it. Three are crossed out, two are the same idea written twice, and one has been sitting there since last autumn. Every few weeks you open it, read all eleven, feel slightly worse, and close it again. The reason the list never resolves is that you keep trying to answer it with taste, when you are sitting on a set of receipts that answers it with evidence.
Why idea lists never converge
An idea list is a list of things you find interesting. That is a genuinely useful input and a terrible decision-making tool, because interest is not ranked by anything except how you feel on the day you read the list. Two of those eleven ideas are almost certainly good. The list itself contains no mechanism for telling you which two.
What you actually want to know is narrow: of the people who have already paid you, what did they buy, what did they buy afterwards, and which of them came back. That is three questions with numeric answers, and none of them require a survey, a focus group or a launch.
The hard part is that your first hundred buyers are a biased sample. They are the people your existing product already suited. They will point you accurately at the thing next door and tell you nothing at all about the room down the corridor. Knowing which kind of decision you are making, adjacent or new, is most of the skill here.
Two ways to decide what comes next
The difference is not sophistication. It is whether the decision is made from a record that exists whether or not you remember to keep it.
| Choosing from a notes app | Choosing from your customer list |
|---|---|
| Ideas ranked by how you feel this week | Options ranked by what people already paid for |
| Buyers are a number in a monthly total | Buyers are individual records with a purchase history and a lifetime value |
| Repeat customers are a vague impression | Repeat customers are a filter you can apply in a second |
| A quiet product is written off as a bad idea | Views, buyers and revenue are separate, so you can see whether it was the offer or the traffic |
| Free downloaders are invisible | Everyone who took a $0 product is on the same list, with an email address |
| Research means asking strangers what they might buy | Research means reading what your own people did buy |
Reading the receipts
Set aside half an hour. Open the customers area of your store.fan dashboard, export the list to CSV if you prefer a spreadsheet, and work through the following in order. Write the answers down as you go, because the pattern usually appears between two of them rather than inside any one.
Half an hour with your own data
0/7A worked example
Suppose you sell a 19 pack of editing presets and have 104 buyers. Twelve of them have bought something a second time, mostly the 8 add-on pack. Your average lifetime value sits a little above 22, but the top twenty rows are closer to 45, and almost all of them bought both packs within a fortnight of each other. Meanwhile a 45 recorded workshop you made in a hurry has 300 views and nine buyers, which is a three per cent conversion on very little traffic.
Read together, those three facts do not point at a new preset pack. They point at the workshop. A meaningful slice of your buyers want more from you within two weeks of the first purchase, they will pay more than once, and the higher-priced product converts at a respectable rate to the tiny number of people who ever see it. Product two is a better version of the workshop, promoted properly to the people who already own the presets. That is a smaller, duller decision than anything on your ideas list, and it is the one the data supports. No promise attaches to it; it is simply the bet with the most evidence behind it.
If your buyer records are currently spread across payment emails and a spreadsheet, this is the part that gets easier first.
Start building the listThe mistake most people make
They do the analysis, discover the answer is the boring adjacent product, and build the exciting one anyway. If that is you, at least be honest about which you are doing, because the two need different expectations. The other common error is going cheaper. When a product does not sell, the instinct is to make a smaller, cheaper version, but the data frequently says the opposite: your highest-value buyers were not price-sensitive, they simply ran out of things to buy. The customer list is where that shows up, and it costs nothing to look at on any plan.
Twenty is enough to spot an adjacency, especially if two or three of them have bought twice. Read the individual records rather than the averages; at that size the average is meaningless and the stories are not.
Ask, but weight it lightly. People are honest and unreliable about future purchases. An order-form question on your next product costs nothing and gives you language to use, while the purchase history tells you what they actually do.
Yes. A $0 lead magnet creates a real record with a real email address, so you can see which free thing precedes which paid purchase, and how long the gap usually is.
Then do not deliver it, but notice what it is telling you. Demand for one-to-one time often means people want a decision made for them, which can sometimes be met with a course, a template or a paid community instead.
The idea list is not useless; it is just the wrong document to decide from. Keep it for inspiration and let the receipts do the ranking. Ten product types can sit on the same page on store.fan, so whichever answer your data gives you, the next thing does not need a new site or a new checkout, only a new entry in the dashboard. The features overview shows what you can add, and the pricing page shows what each plan includes, with 0% platform fee on all of them.
Get the record started now and product three will be an easier decision than product two was.
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