An ecommerce product strategy states which shoppers the store is built for, which parts of finding, choosing, buying and reordering it will make better than the alternatives, and what it will leave out. It is owned by the head of product and agreed with the chief executive, merchandising, marketing and operations.
This is the Ecommerce version of the product strategy template.
A complete product strategy for a fictional organization: online retailer of bicycle parts and accessories for riders who maintain their own bikes.
| Organization | Online retailer of bicycle parts and accessories for riders who maintain their own bikes (50 staff) |
|---|---|
| Ambition | Be the store where a home mechanic knows a part fits before buying it, and grow sales from $24M to $27M on the same paid traffic. |
| Horizon | 1 year |
The store took 252,000 orders worth $24M this year from 9.6 million sessions, a 2.6% conversion rate at a $95 average order. A product team of six engineers runs the site. Phones bring 68% of sessions but convert at 1.7%, against 4.5% on desktop. The catalog holds 38,000 SKUs, and 11,000 of them sold fewer than three units. Customers return 11.5% of orders, and 44% of returns are parts that did not fit the bike. Paid acquisition now costs $31 per new customer against a first-order contribution of $19, and only 34% of first-time buyers order again within 12 months.
Challenges| Vision | A rider tells the store which bikes they own once. From then on every search, category and product page shows what fits those bikes, checkout takes under a minute on a phone, and a worn part is two taps away from being reordered. |
|---|---|
| Time frame | Two years for the full vision. This strategy covers the 12 months to the end of Q4 2027 and is judged on wrong-fit returns, mobile conversion and the 12-month repeat rate. |
| Target customer | A rider who owns two or more bikes, does most repairs and upgrades at home, and places three or four parts orders a year worth about $300 in total. They know what they want to fix but not always which standard their bike uses. |
|---|---|
| Problem | Bike parts come in dozens of overlapping standards for axles, freehubs, bottom brackets, brake mounts and drivetrain speeds. A product page lists specifications, but the shopper has to work out whether they match the bike in the garage. A wrong guess means a return and a bike off the road for another week. |
| Current alternative | Forum threads, manufacturer compatibility charts in PDF, a call to a local bike shop, or a large marketplace with a bigger assortment and no fit help at all. Many buy the part they had before because it is the only one they are sure of. |
| Why now | Cost per new customer has risen from $22 to $31 in two years while first-order contribution is $19, so growth has to come from conversion and repeat orders. Three years of order and return records now show which parts customers kept and which they sent back as not fitting. |
| We are the only | Online parts store that confirms fit against the shopper's own bike on every product page, for riders who do their own maintenance. |
|---|---|
| Differentiators | A saved bike profile that filters search and categories to compatible parts. Fit data built from our own returns and checked by staff mechanics. A two-step phone checkout. Reorder prompts timed from each customer's purchase history. |
| Where we will not compete | The widest catalog or the lowest price on every item. Complete bikes, clothing and nutrition as growth categories. Riders who want a shop to do the work, who are better served locally. |
| Bet | Hypothesis | Evidence so far | Investment |
|---|---|---|---|
| Fit confirmation from a saved bike | Showing whether a part fits the shopper's bike raises conversion in fit-critical categories and halves their wrong-fit returns | A compatibility checker on 600 cassette and chain SKUs lifted add-to-cart by 14% and cut returns on those SKUs by half | 3 engineers and 1 designer all year; 2 staff mechanics building fit data for 9,000 SKUs |
| Two-step mobile checkout | Guest checkout and wallet payments lift mobile checkout completion from 41% to 55% | 38% of mobile checkout exits happen at account creation; desktop completion is 58% | 2 engineers for the first two quarters |
| Reorders for wear parts | Prompts timed from a customer's own purchase history lift the 12-month repeat rate from 34% to 42% | An email to 8,000 chain buyers six months after purchase drew a 9% reorder rate against 3% for a control group | 1 engineer from the third quarter; lifecycle marketing manager |
| A smaller, better-described catalog | Removing slow SKUs and enriching the best sellers improves search results and stock availability | The top 6,000 SKUs bring 81% of revenue; the slowest 11,000 bring 1.5% and 9% of support contacts | 1 engineer on search all year; 3 merchandisers |
Priorities and measures
Uncertainty about fit is the main reason these shoppers hesitate and the cause of 44% of returns. It is also the one thing a large marketplace does not do for them.
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| Orders returned because the part did not fit | 5.1% | 3% | Q4 2027 |
| Conversion rate in the four fit-critical categories | 2.9% | 3.6% | Q4 2027 |
| Orders placed by customers with a saved bike | 0% | 25% | Q4 2027 |
Phones carry 68% of sessions and convert at less than half the desktop rate. Checkout is where the gap is widest and the fix is best understood.
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| Mobile checkout completion | 41% | 55% | Q3 2027 |
| Mobile conversion rate | 1.7% | 2.2% | Q4 2027 |
| Sitewide conversion rate | 2.6% | 3% | Q4 2027 |
A first order loses $12 after acquisition cost, and chains, tires, brake pads and cables are 41% of orders. Customers who return for them are what make the first order worth buying.
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| First-time buyers who order again within 12 months | 34% | 42% | Q4 2027 |
| Revenue from returning customers | 52% | 58% | Q4 2027 |
Eleven thousand SKUs bring 1.5% of revenue and 9% of support contacts, while best sellers go out of stock. A tighter catalog makes fit data, search and buying easier to get right.
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| In-stock rate on the top 2,000 SKUs | 88% | 96% | Q4 2027 |
| Site searches that return no results | 17% | 6% | Q3 2027 |
| Active SKUs in the catalog | 38K SKUs | 27K SKUs | Q2 2027 |
The same structure with a prompt in every field. Copy it, or download it as a Word or Excel file.
| Organization | [Describe your organization in a few words, with its size] |
|---|---|
| Ambition | [One sentence on where you want to be at the end of the plan] |
| Horizon | [How long the plan runs, for example 12 months] |
[Where things stand today: the facts that make this strategy necessary]
Challenges| Vision | [Your vision] |
|---|---|
| Time frame | [Your time frame] |
| Target customer | [Your target customer] |
|---|---|
| Problem | [Your problem] |
| Current alternative | [Your current alternative] |
| Why now | [Your why now] |
| We are the only | [Your we are the only] |
|---|---|
| Differentiators | [Your differentiators] |
| Where we will not compete | [Your where we will not compete] |
| Bet | Hypothesis | Evidence so far | Investment |
|---|---|---|---|
| [Bet] | [Hypothesis] | [Evidence so far] | [Investment] |
| [Bet] | [Hypothesis] | [Evidence so far] | [Investment] |
| [Bet] | [Hypothesis] | [Evidence so far] | [Investment] |
Priorities and measures
[Why this priority matters now, in one or two sentences]
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
[Why this priority matters now, in one or two sentences]
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
[Why this priority matters now, in one or two sentences]
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
[Why this priority matters now, in one or two sentences]
| Outcome | Baseline | Target | Due |
|---|---|---|---|
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
| [Metric you will track] | [Where it is today] | [Where it should be] | [When] |
Start from the funnel by device and by category: sessions, add-to-cart, checkout completion, returns and repeat rate. The widest gap between segments usually points to the first bet.
Name the shopper's real uncertainty for your category. For parts it is fit; for clothing it may be size, for furniture delivery, for food freshness. Build the differentiator around removing it.
Read return reasons and site search logs before choosing features. They are the cheapest research an online store has.
Work out first-order contribution after acquisition cost. If it is negative, repeat purchase belongs in the product strategy, not only in the marketing plan.
Match the number of bets to the engineering team. With six engineers, four bets is the limit, and two of them should share people in sequence.
Agree the assortment decisions with merchandising in the same document. The catalog is part of the product a shopper experiences.
A plan only works if it is reviewed on a rhythm. This is the cadence the example assumes.
| Check-in | Outcome owners update progress and confidence weekly. |
|---|---|
| Review | Priority owners review outcomes and unblock initiatives monthly. |
| Reset | Leadership revisits priorities and targets quarterly. |
Tability keeps this cadence for you. Each priority becomes an objective, each outcome a key result with its baseline and target, and each initiative a tracked task. Owners get a check-in reminder and the plan shows what is on track.
Track this plan in TabilityStill comparing tools? See the 10 best strategy software tools.
It covers the shopping experience as a product: how shoppers find items, judge whether an item is right for them, pay and come back. It names the target shopper, the problem the store solves better than alternatives, and a few bets with evidence. Assortment and stock belong in it too, because they shape what the shopper sees.
A merchandising strategy decides what to sell, at what price and in what depth. A product strategy decides how the store helps a shopper choose and buy it. They overlap on assortment and product data, so they should be agreed together. In this example the catalog is cut from 38,000 SKUs to 27,000 as one of four product bets.
Track conversion rate by device, checkout completion, return rate by reason and the share of first-time buyers who order again. Add a measure for each bet, such as searches with no results or orders from customers with a saved profile. Revenue and average order value are useful context but are too broad to show whether a product bet worked.
Usually not before the mobile website converts well. An app mainly serves repeat customers, so it pays off only once repeat purchase is established and the checkout already works on a phone. This example has 68% of sessions on phones and still defers an app, because mobile checkout completion is 41% and guest checkout is the cheaper fix.
Three or four, with a named person on each. A team of six engineers can run two bets at full strength or four if some run in sequence. More than that leaves each bet half-built at the end of the year. Write down the evidence behind each bet and what result would end it.
Be the field service product a contractor with 5 to 49 technicians can set up in two weeks and that technicians choose to use, taking net revenue retention from 97% to 104%.
Be the primary operating account for half of our small business customers by mid 2028, so the bank's cheapest deposits grow again.
A product strategy states who the product is for, which problems it will solve first, and why customers will choose it over the alternatives.
Be the field service product a contractor with 5 to 49 technicians can set up in two weeks and that technicians choose to use, taking net revenue retention from 97% to 104%.
Be the primary operating account for half of our small business customers by mid 2028, so the bank's cheapest deposits grow again.
Product strategy example
Horizon: 1 year
4 priorities · 11 outcomes
Targets are illustrative. Adapt them to your baseline before you start.