Free Share of Wallet Survey Template
Measure how customers split category spend between you and competitors, using a single consistent time window and a buyer-qualified invite list. Quantify competitive leakage, find high-wallet accounts with low share, and turn the results into a focused retention and expansion plan.
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Core Share of Wallet Questions (with customization rules)
"In the last 90 days (edit to 30 or 180 to match your purchase cycle), have you personally purchased in this category for yourself/your household (or for your company)?"
Why it matters: Share of wallet only works if you ask real category buyers about the same time window you will use for allocation.
When to use: Put this first. If they say "No," end the survey (or route to a different questionnaire).
"Thinking about the last 90 days (edit to 30 or 180), which brands have you purchased from in this category? (Type any you remember.)"
Why it matters: Unaided recall captures top-of-mind competitors and keeps your aided list shorter (and more believable).
When to use: Ask before you show any brand list. Use the entries to pre-select brands in the next question when possible.
"Which of the following brands have you purchased from in this category in the last 90 days (edit to 30 or 180)? (Select all that apply.)"
Why it matters: This is your aided check. It closes gaps from unaided recall without forcing everyone through an exhaustive competitor list.
When to use: Show your brand + your top competitors + "Other (please specify)." If they select a brand, then ask allocation only for selected brands.
"Which ONE brand did you spend the most with for this category in the last 90 days (edit to 30 or 180)?"
Why it matters: A primary brand flag is easy to answer and gives you a stable cut even when percent allocations are noisy.
When to use: Ask right before the allocation item. Use it to sanity-check allocations (primary brand should usually have the highest share).
"Best estimate: About what percent of your total category spend in the last 90 days (edit to 30 or 180) went to each brand? (Your answers should add up to 100%.)"
Why it matters: This is the core share-of-wallet measure. Percent splits are fast for buyers and easy to trend.
When to use: Ask only for the brands they selected as "purchased." Include "Prefer not to say" and allow "I am not sure" to reduce guessing.
"What is the main reason you spent more with the brand you chose above than other brands in the last 90 days (edit to 30 or 180)?"
Why it matters: Allocation without a reason is hard to act on. This question gives you the most direct driver to fix or defend.
When to use: Ask after you know their primary brand. Offer a short list (price, selection, quality, convenience, service, trust) plus "Other."
"What would make you allocate more of your category spend to our brand in the next 90 days (edit to 30 or 180)?"
Why it matters: This turns leakage into a concrete to-do list (product gaps, pricing, availability, onboarding, and messaging).
When to use: Ask everyone who is not 100% with you. Keep the list short and map each option to an owner.
Time window discipline: Pick one window (for example, 90 days) and use it in every behavior, brand-usage, and allocation question. Do not mix "last month" with "last year" in the same run.
Competitor list mechanics: Ask unaided brands first, then show a short aided list, then branch the allocation item so people only allocate across brands they said they bought.
Sensitivity and effort options: Use "best estimate" language, allow an "I am not sure" or "Prefer not to say" option, and consider ranges/bands instead of exact numbers when you expect people to guess or drop off. Expenditure reporting is often imperfect, so design for honest uncertainty rather than forced precision.
Optional module (tie SOW to experience signals): Add 1-2 loyalty items after allocation so you can test whether experience measures actually move wallet allocation. A common pattern is to ask overall satisfaction and likelihood to repurchase, then compare those scores across low vs high SOW groups; prior work shows satisfaction and SOW do not always move in lockstep, so you should validate the relationship in your category (A Longitudinal Analysis of Customer Satisfaction and Share of Wallet).
- Satisfaction: "Overall, how satisfied are you with our brand for this category?" (5-point scale)
- Repurchase intent: "How likely are you to buy from us again in the next 90 days?" (0-10; edit the window to match the survey)
Got the questions set? Next, make sure you are inviting real category buyers.
Who to Invite (and how to screen for real category buyers)
Goal: Invite the right people so your share-of-wallet numbers reflect real buying, not guesses. Start with a clean invite list, then screen to confirm the person bought in the same time window you will use for allocation (for example, the last 90 days).
- Set: Clean invite list + purchase-within-window screener + role checks (for B2B).
- Default: Invite current customers who bought in the last 90 days, then screen out non-buyers before you ask any allocation questions (edit the window to 30 or 180 days to match your purchase cycle).
Invite list: Build your list from CRM, subscription records, or recent transaction logs, then sanity-check coverage gaps (missing regions, channels, or account sizes) in your sampling plan.
Screen for real buyers: Use simple screeners that match your allocation time window. If someone did not buy in-window, end the survey or route them to an awareness survey instead.
- Recent purchase: "In the last 90 days, did you purchase in this category?" (Yes/No; edit window to match the survey)
- Purchase frequency: "How often do you buy in this category?" (Weekly / Monthly / Quarterly / Less often)
- Channel qualifier (optional): "Where did you buy most recently in this category?" (Online / Retail / Distributor / Other)
Role check: Ask "Are you responsible for selecting or purchasing in this category for your team/account?" If they are not, route to a shorter perception module or end the survey.
Multi-buyer accounts: If purchasing is shared, collect answers from 2-3 roles (for example, procurement + admin user + budget owner) and compare them. If you can only survey one person, target the role closest to ordering and billing.
Track field results: Record outcomes (delivered, opened, started, completed, screened out) so you can report consistent outcome rates using AAPOR Standard Definitions.
Interpret low response carefully: Low response does not automatically mean your data is wrong, but it can change who you heard from. Compare early vs late responders and key customer attributes to spot potential bias, and use the guidance in What low response rates mean for telephone surveys as a practical checklist.
Ready to size the effort? Next, set a completes target that is stable enough to act on.
Recommended Sample Size for Stable SOW Reads (overall and by segment)
Directional overall read
Internal starter target: 150-200 qualified completes if you mainly need a first cut of overall SOW, top competitors, and the biggest leakage pockets (adjust after your baseline and category variability). Then act on only the largest gaps (not small point differences).
Quarter-over-quarter tracking
Internal starter target: 300-500 qualified completes per wave for more stable trending on overall SOW and the top 3-5 competitors (adjust after your baseline). Keep the time window and brand list fixed so the trend reflects behavior, not questionnaire drift.
Segment cuts you can safely act on
Internal starter target: 100+ qualified completes per key segment before you change pricing, onboarding, or messaging for that segment. Treat smaller subgroups as directional only and combine them until you reach your threshold.
Control your mix (so one segment does not dominate)
Distribute invites across the segments you plan to read out (region, tier, industry, acquisition channel). If your customer file is uneven, set quotas up front or weight results after the fact and document the choice alongside your sample size guidance.
- Cadence default: Run quarterly for fast-moving categories; run twice per year for longer purchase cycles.
- Event-based waves: Add a wave after a major price change, packaging change, or product launch, but keep the same time window so results stay comparable.
For practical sample design and how to distribute invitations across key groups, see the UN guidance on Designing Household Survey Samples.
Completes set? Next, turn responses into SOW, leakage, and a prioritized opportunity list.
Results Playbook: Calculate SOW, Leakage, and the Opportunity Map
- Step 1: Clean and validate the allocation answers
Check that percent splits add to 100% (or fall within an acceptable range like 95-105% if you want a soft check). If the total is off, prompt for a fix in-survey, or normalize to 100% in analysis and flag the record.
- Drop records that fail the buyer screener or have impossible patterns (e.g., 0% to every selected brand).
- Keep "Prefer not to say" as missing, and report the missing rate as a quality metric.
- Step 2: Calculate customer-level share of wallet (SOW)
Use the simplest definition: Your SOW = (your spend with your brand) / (total category spend). If you collected percent allocation, your SOW is that percent for your brand.
Worked example: If a customer allocates 40% to you, then their SOW = 0.40.
Act on it by tagging each account: 0-20%, 21-50%, 51-80%, 81-100% so your team can target plays by band.
- Step 3: Calculate leakage and competitor-specific leakage
Compute Leakage = 1 - Your SOW. Then break leakage out by competitor to see where money is going (Competitor A%, Competitor B%, Other%).
Worked example: If Your SOW = 0.40, then Leakage = 0.60. Now you know the expansion ceiling for that customer is 60 points.
Use this to pick the right fix: price and packaging for one competitor, availability for another, and service or onboarding for a third.
- Step 4: Roll up results by segment (use medians and mix metrics)
Summarize each segment with a small set of stable outputs: median SOW, % where you are primary brand, and top competitor leakage. Medians resist outliers and keep your readouts steady.
- Segment by: plan tier, tenure, industry, region, channel, and the competitor they named as primary.
- Run a simple driver cut: compare median SOW for people who selected each driver (price, selection, convenience, service).
- Step 5: Build the opportunity map (Wallet Size x Your SOW)
Combine how big the wallet is with how much you get. Research links both wallet size and share to customer outcomes, so you should prioritize accounts with large wallets and low share (Size and Share of Customer Wallet).
Quadrant What it means Next best action High wallet / Low SOW Big category spend, but they split heavily to competitors Expansion plan: onboarding fixes, cross-sell, competitive counter-offer, remove friction High wallet / High SOW High value and already concentrated with you Retention plan: service guarantees, advocacy, lock in renewals, protect against switching triggers Low wallet / Low SOW Small category spend and low share Low-touch nurture: lifecycle messaging, light bundles, self-serve education Low wallet / High SOW They prefer you, but the category is small for them Grow wallet: new use cases, bundles, frequency drivers, referrals Define wallet size using a simple band question (e.g., "$0-$99 / $100-$249 / $250+") if you did not capture exact spend.
- Step 6: Translate findings into owners, experiments, and a dashboard
Turn each top driver and switching trigger into a named owner and a test you can run in 30 days. Then track whether targeted segments move up a SOW band next wave.
- Product gaps: fix missing features, assortment, integrations
- Pricing/packaging: adjust tiers, bundles, and discounts for high-wallet/low-SOW
- Channel/friction: improve availability, shipping, billing, procurement steps
- Onboarding/cross-sell: create plays by primary competitor and by driver
- Messaging: write counter-messaging for the top leakage competitor
If you added experience items, read them alongside brand loyalty metrics (NPS/CSAT/CES) to avoid assuming attitudinal loyalty equals wallet share. Act on the combination (for example: high NPS but low SOW usually means unmet needs, constraints, or convenience issues).
Now pressure-test your setup. Next, fix the common mistakes that make SOW surveys hard to trust.
Common Share of Wallet Survey Mistakes (and how to avoid bad data)
Mistake: Mixing time windows. Fix: Pick one window (for example, 90 days) and repeat it everywhere (screeners, brand usage, allocation, and drivers) so people do not contradict themselves.
Mistake: Confusing SOW with market share. Fix: Keep your wording customer-level: "your spend" and "your total category spend." Market share is about total market sales; SOW is within-customer allocation.
Mistake: Forcing exact dollars. Fix: Use percent splits or spend ranges with "best estimate" language, plus "I am not sure" and "Prefer not to say." Spend reporting is often imperfect, so design for honest uncertainty rather than forced precision (Measuring What We Spend: Toward a New Consumer Expenditure Survey).
Mistake: Showing a huge competitor list to everyone. Fix: Ask unaided first, then show a short aided list, then branch allocation only to brands they selected as used.
Soft validation: Add a gentle check for totals ("Your answers add to 85%. Do you want to adjust?") instead of a hard error that causes drop-off.
Leading wording: Keep brand descriptions neutral and keep the order randomized where possible. Then review your draft for response bias risks (loaded options, unequal detail, and forced choices).
Over-segmentation: Do not slice into tiny subgroups and declare a shift. Fix: Pre-register 5-8 segments you will act on, and hold the rest for exploration.
Frequently Asked Questions
What is share of wallet (and how is it different from market share)?
Share of wallet (SOW) is the percent of a single customer's category spend that goes to your brand. Market share is your percent of total category sales across the whole market.
Use SOW to decide which existing customers to expand or retain, because you can often raise SOW within your base even when overall market share is flat.
Should I ask customers for exact spend dollars or percent allocation?
Use percent allocation (or spend ranges/bands) as your default because it is faster to answer and reduces drop-off. Add "best estimate" language plus an "I am not sure" or "Prefer not to say" option so people do not fabricate precision.
Ask for exact dollars only when you truly need it (often in high-value B2B) and you can support it with context, like a recent invoice range or prefilled last purchase amount.
What time window should I use for a share of wallet survey?
Match the window to the purchase cycle: 30 days for frequent purchases, 90 days for monthly/quarterly cycles, and 180 days for infrequent categories. Then keep that same window in every screener, brand-usage item, and allocation question.
If you change windows mid-survey, you will get contradictions that look like "bad data" but are really bad setup.
How do I handle a long competitor list without making the survey too long?
Start with unaided recall (open text), then show a short aided list of the brands you care about, plus "Other (please specify)." Next, branch the allocation question so people only allocate across brands they said they used.
If you require totals to equal 100%, use a soft check and allow "Other" without breaking the logic (for example, let "Other" be a single bucket rather than a long tail of brand entries).
How many responses do I need to compare segments or track quarter over quarter?
For a first directional read, aim for 150-200 qualified completes overall. For quarter-over-quarter tracking, aim for 300-500 per wave and keep the time window and brand list the same.
For segments you will act on, use 100+ completes per key segment as a practical minimum; treat smaller cuts as directional and combine them until you reach your threshold.
How do I turn leakage findings into an action plan?
Build a wallet-size x SOW map and prioritize "high wallet / low SOW" accounts for expansion plays, while protecting "high wallet / high SOW" accounts with retention and advocacy actions. Put "low wallet / low SOW" into low-touch nurture, and use "low wallet / high SOW" to grow category usage.
Then assign owners to the top drivers of allocation (price, selection, service, convenience) and run one experiment per driver so you can measure SOW movement next wave.
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