Research: What Physical Retail Stores Deliver in a Digital Economy
Ayşe Çetinel, Gürhan Kök, Robert Rooderkerk · article · 2026-08-18 source ↗ Reader 🖥️
A physical store's value should be measured and organized around its total, causally-isolated contribution to enterprise-wide customer value across channels and the whole customer journey — not by siloed channel P&L or raw post-opening sales — and that value is concentrated in specific customer-journey moments and product categories, so investment should be matched to where it demonstrably helps rather than spread evenly across the assortment.
practical · mixed — An HBR 'research digest' piece: it reports a quasi-experimental empirical study (theoretical/expository core) but is structured entirely in service of practical prescriptions for retail leaders — how to invest in, evaluate, and organize physical stores.
Structure
| Part | Role |
|---|---|
| Opening countertrend narrative: digital-native and established retailers (Warby Parker, Ulta Beauty, Action, Rituals, Coolblue) are accelerating physical store openings despite e-commerce growth. | context / motivation |
| Reframing: the live question is not whether physical retail has a future but how to invest in it, and this is especially hard for multi-brand retailers who lack single-brand exclusivity and risk pure showrooming. | problem statement |
| Methodology: 26 months of transaction data across 2,388 postal-code areas around three store openings, matched-comparison analysis, plus a 450-consumer survey. | evidence base |
| 'Stop Thinking in Terms of Channels': critique of channel-siloed P&L evaluation, presentation of the causal revenue effects for the three store openings. | core argument + evidence |
| 'Give Every Physical Touchpoint a Clear Job': prescriptive framework built on three customer-journey value stages (information/decision, fulfillment, returns), illustrated by Target and Ulta Beauty. | prescription + example |
| 'Don't Spread the Experience Evenly': category-level survey and revenue findings distinguishing destination categories from accessories. | evidence refining the prescription |
| 'Organize Around Customer Value': organizational prescription — cross-functional ownership, unified cross-channel metrics and incentives. | conclusion / call to action |
| Closing paragraph restating the thesis in compressed form. | conclusion |
Key terms
- destination categories
Product categories (e.g. televisions, laptops, mobile phones) where customers' perceived in-store value during information search and immediate fulfillment closely predicts revenue uplift, and where the store is the driver of the visit. - showrooming Omnichannel Value Attribution
Customers examining a product in-store but ultimately buying it elsewhere for a lower price or more convenient delivery — the specific risk multi-brand (non-exclusive) retailers face that single-brand retailers largely avoid. - total net revenue Omnichannel Value Attribution
Net revenue (purchases minus returns) summed across online and store channels for a matched geographic area, used as the enterprise-wide performance metric that should replace channel-specific figures. - halo effect
Used skeptically here: the common assumption that online sales growth following a store opening reflects a positive spillover from the store — a label the authors warn can be applied to online growth that 'would have occurred anyway,' i.e., mistaken for causal impact without a counterfactual. - job (of a physical touchpoint)
The specific customer problem a location is meant to solve — information search/decision, immediate fulfillment, or returns/post-purchase resolution — which should be defined before choosing store format or location. - activation vs. acquisition
Two distinct growth mechanisms for a store: activation means increasing purchase frequency/spending among existing customers; acquisition means bringing in customers new to the retailer. The study finds large stores grow mainly via activation.
Propositions
- explicitPhysical stores should be evaluated by their total, causally-isolated contribution to net revenue across all channels and throughout the customer journey — not in isolation, and not solely by their effect on online sales.conf: high
- explicitChannel-siloed P&L structures (separate P&Ls for stores vs. e-commerce) distort how store openings get evaluated, because each side is incentivized to defend its own channel's revenue.conf: highsupportsDon't Let AI Make Bad Analytics Worse · p9 — The channel-P&L 'defend your own revenue' dynamic is a structural analog of the incentive-driven distortion described there: local success metrics push both stores and e-commerce toward framings that protect their own budget rather than surface the true causal picture.
- explicitWhat matters in evaluating a store opening is the change in revenue caused by the store, isolated via matched-area comparison, not simply what happened after the opening — since post-opening online declines can reflect substitution and post-opening online growth can be wrongly credited as a halo effect that would have occurred anyway.conf: highextendsDon't Let AI Make Bad Analytics Worse · p5 — Applies the descriptive/predictive/causal rigor principle concretely to retail investment: insists that a store's post-opening sales figures be tested via matched-comparison counterfactual before being read as caused by the store, rather than treated as causal at face value.
- explicitIn the study, all three store openings reduced nearby online net revenue by roughly 8% to 11% within the first four months.conf: high
- explicitThe two large, experience-centric stores more than offset that online cannibalization, increasing total net revenue across channels by 21.7% and 23.2% (reaching 27.5% at the store observed longer), while the smaller convenience-centric store cannibalized a similar share of online sales but produced no significant increase in total net revenue.conf: high
- explicitThe performance gap between store formats was not primarily explained by differences in product assortment or category coverage — restricting the comparison to categories carried by both formats barely changed the large stores' gains — but by what customers could do inside the store.conf: high
- explicitThe large stores' revenue growth came more from activating and deepening relationships with existing customers, who purchased more frequently, than from acquiring new customers — though new-customer acquisition also contributed substantially.conf: high
- explicitCannibalization of online sales was highly local, concentrated nearest the stores — the same areas where total revenue gains were strongest — so a store functions as much as an activation engine as an acquisition channel.conf: high
- explicitA physical touchpoint's investment should be defined by a specific customer-problem 'job' — information search/decision-making, immediate fulfillment, or returns/post-purchase resolution — chosen before the store's format or location is chosen; a store should not simply reproduce what customers can already do online.conf: high
- explicitFor 'destination categories' (e.g. televisions, laptops, mobile phones), perceived in-store value during information search and immediate fulfillment closely predicts revenue uplift, while ease of returns matters much less.conf: high
- explicitFor accessory categories, none of the surveyed in-store value perceptions (sensory evaluation, expert advice, immediate access, easier returns) explained revenue performance; their gains arose mainly through cross-selling with destination products.conf: high
- explicitEven within a successful, experience-centric store, more than four in ten product categories generated no measurable revenue uplift — aggregate store-level success conceals substantial category-level variation.conf: high
- explicitPhysical investment — space, inventory, technology, staff expertise — should be concentrated selectively by category/customer-problem fit rather than spread evenly across the assortment.conf: high
- explicitThe category-allocation principle generalizes beyond retail — e.g. concentrating bank-branch expertise on complex financial decisions, or reserving B2B demonstration centers for solutions that are hard to evaluate remotely.conf: medium
- explicitOrganizationally, a senior leader or cross-functional team should own the customer-journey proposition across channels; customer data, inventory visibility, budgets, and decision rights should not remain divided by channel, and incentives should reward enterprise-wide value creation rather than protecting individual channel or functional budgets.conf: high
- implicitThe matched-comparison-area research design adequately isolates the causal effect of a store opening from confounds such as regional demand trends, concurrent marketing, competitor actions, and seasonality, licensing the causal language ('the change caused by the store') used throughout the piece.conf: medium
- implicitRetailers can feasibly restructure decision rights, data ownership, and incentive/compensation design across channels — i.e. the main obstacle to enterprise-wide value evaluation is measurement and organizational-design choice, not deeper structural constraints such as store-manager compensation tied to local P&L, real-estate lease structures, or labor agreements.conf: medium
- implicitFindings from three store openings at one online-first, multi-brand electronics retailer are treated as sufficiently representative to generalize a category-allocation and channel-evaluation principle to retail — and, by extension, to banking and B2B — more broadly.conf: medium
Arguments
A physical store's opening should be evaluated by its total, causally-measured net-revenue effect across all channels, not by channel-siloed P&L or by raw post-opening sales levels. strength: medium
Explicit premises:
- Separate store/e-commerce P&Ls create incentives for each side to defend its own revenue, distorting how openings are read.
- Post-opening online declines can reflect substitution rather than store failure, and post-opening online growth can be wrongly credited as a halo effect that would have occurred anyway.
- Matched-comparison-area analysis isolates the incremental effect of the store from underlying trends.
- Empirically, the large stores turned 8-11% online cannibalization into a 21.7-27.5% total net revenue gain, while the small store's similar cannibalization produced no net gain — showing channel-level numbers alone are misleading.
Implicit premises:
- The matched-comparison design validly removes confounding (selection, regional trend, marketing, competitor) bias, licensing the causal language used.
- Once measured this way, leaders are able and willing to act on total net revenue as the decision metric — the organizational and technical capacity to compute and report it exists or can be built.
Inferences:
- If total net revenue is the correct yardstick, individual channel managers arguably should not be evaluated or compensated primarily on channel-specific P&L targets — a compensation-design implication the article gestures toward ('incentives should reward enterprise-wide value') but never works out mechanically.
Physical investment (space, inventory, technology, staffing) should be concentrated on 'destination' categories and specific customer-journey moments rather than spread evenly across the assortment. strength: medium
Explicit premises:
- Survey-measured in-store value perceptions (information search, fulfillment) predict revenue uplift for destination categories.
- The same perceptions do not predict revenue for accessory categories, whose gains instead trace to cross-selling.
- More than four in ten categories in a successful store showed no measurable uplift at all.
Implicit premises:
- Self-reported survey value-perceptions causally (or at least reliably predictively) reflect the actual behavioral driver of the observed revenue uplift, rather than merely correlating with it for some other reason.
Narratives
- Warby Parker, Ulta Beauty, and the Dutch retailers Action, Rituals, and Coolblue are all accelerating physical store openings despite operating in digitally mature markets.
→ Establishes the countertrend premise that motivates the whole piece: physical retail decline is not a simple wind-down, so the live question is how to invest, not whether to. - Target's stores operate simultaneously as shopping destinations and fulfillment hubs for digitally originated orders.
→ Illustrates the 'interdependence' and 'give every touchpoint a clear job' propositions with a recognizable brand example, standing in for the anonymized study retailer. - Ulta Beauty's chief retail officer Amiee Bayer-Thomas describing the retailer's mission as needing to 'show up for the local guest.'
→ Supports the 'define the customer problem first' proposition with a practitioner's own framing, lending face validity to the academic argument. - Coolblue displays accessories alongside primary products or bundles them into use-case settings such as complete home-office configurations.
→ Illustrates and supports the cross-selling explanation for why accessory categories perform well despite offering no hands-on in-store experience of their own.
Questions addressed
- ✅ Should retailers still invest in physical stores at all, given e-commerce growth and closures on many high streets?
Yes — reframed: the relevant question is no longer whether but how to invest. - ✅ How should a store's value be measured, given that it can shift revenue across channels rather than simply add to them?
By total net revenue across channels, measured via matched-area causal comparison rather than channel-siloed accounting. - ✅ Which categories or customer needs justify a rich, resource-intensive in-store experience?
'Destination' categories where in-store information-search and fulfillment value is high; accessories benefit more from cross-selling placement than standalone experience. - ✅ How should retail organizations be structured to capture cross-channel store value?
Cross-functional/cross-channel ownership of the customer-journey proposition, with unified data, budgets, decision rights, and enterprise-wide incentives. - ⭕ How should channel-specific accountability and compensation actually be redesigned in practice, given that removing channel P&Ls creates its own ownership problem (who is accountable when the enterprise-wide number is bad)?
- ⭕ Does the 'activation of existing customers' advantage of experience-centric stores persist as competitors adopt similar formats in the same category, or does it erode once the experiential differentiation becomes commonplace?
Gaps
- incompleteThe causal claims rest on three store openings at a single online-first, multi-brand electronics retailer over 26 months; there is no discussion of statistical power, confidence intervals, or whether the findings would generalize to other categories (grocery, apparel, home goods) or to retailers of different sizes.
Read next: The underlying academic paper in Production and Operations Management, or the broader empirical literature on store-opening halo/cannibalization effects (e.g. work by Avery, Steenburgh, Deighton, or Bell, Gallino, Moreno on online-offline retail interactions) for a larger-sample causal estimate. - incompleteThe article never explains how the 'matched comparison areas' were selected or validated — what covariates were matched on, whether parallel pre-trends were checked — so a reader cannot independently assess whether the causal identification is credible or simply asserted.
Read next: The forthcoming Production and Operations Management paper, which presumably documents the matching methodology in full. - illogicalThe piece frames 'cannibalization was highly local, precisely where total revenue gains were strongest' as a benign co-location for the large stores, but never explains why the same local-activation mechanism apparently failed to fire for the small convenience-centric store, which cannibalized online sales 'by a similar amount' yet produced no net gain. The mechanism gap (why activation worked for one format and not the other) is asserted away with 'what customers could do inside them' rather than examined.
Read next: Category- or format-segmented customer survey data the article summarizes but doesn't share; or further work isolating which specific in-store capabilities (staffing depth, product-testing setup, layout) differed between the large and small formats. - incompleteNo discussion of the capital cost or ROI timeframe of large experience-centric stores versus small convenience-centric ones. A 21-27% total net revenue uplift is not directly comparable across formats without knowing their relative capex/opex — a store with a smaller revenue lift could still be the better investment if it costs proportionally much less.
Read next: Retail real-estate and store-format economics literature, or a follow-up piece modeling store-format payback/ROI rather than revenue uplift alone. - incompleteThe organizational prescription — that incentives should reward enterprise-wide value creation rather than protecting individual channel or functional budgets — is asserted with no example of any company that has actually redesigned compensation or accountability structures this way. This is the least-evidenced part of the piece, in contrast to the well-evidenced store-opening effects.
Read next: Organizational-design and compensation literature on decentralized P&L versus matrixed cross-channel accountability.