Consumer & Omnichannel Growth Consultancy
Growth diagnostics for brands and retailers trading across stores and digital
When customers move freely between search, store, call centre and app before they buy, single-channel metrics stop describing the business. This is a review of how demand actually moves across your estate, where it gets measured badly, and where investment and store operations are pulling against each other.
Who this is for
- Retailers with a store or showroom estate alongside ecommerce
- Consumer brands selling direct, through concessions, or via distributors
- Businesses with call centres or appointment-led assisted sales
- Multi-brand or multi-fascia groups managing shared customers across formats
- Leadership teams where store and digital P&Ls are reported, incentivised or led separately
01 — The model
What growth looks like in this model
- 01
Demand is planned by total customer value, not by channel silo
Marketing, store and CRM investment decisions are made against a shared view of what a customer is worth across every place they transact, not against channel-reported revenue that double-counts or under-counts the same customer.
- 02
Digital and physical reinforce each other deliberately
Store locator usage, click & collect, appointment booking and local search are treated as growth levers in their own right, with the same rigour applied to their measurement as to paid media.
- 03
Local demand is read at store or catchment level
Growth decisions account for the fact that a search uplift, a promotion or a competitor opening plays out differently store by store, not as a single national average.
- 04
Assisted and offline conversion are counted, not guessed at
Store staff, call centre agents and showroom teams are recognised as part of the conversion path, with enough instrumentation to know roughly how much of their influence is real rather than assumed.
02 — Constraints
Where growth usually gets stuck
01
Channels are measured, funded and incentivised separately
Ecommerce is judged on ecommerce revenue, stores on store revenue, and nobody owns the customer who researched online, called the showroom, and bought in person. Budget follows whichever channel can claim the sale in its own system, which is rarely the channel that actually created the demand.
02
Digital influence on physical sales isn't measured
Store locator visits, product research, and 'near me' searches sit upstream of a large share of in-store revenue, but with no consistent way to connect them, digital gets judged only on transactions it can directly close and is chronically undervalued or, sometimes, overcredited.
03
Customer identity fragments across systems
Loyalty, POS, ecommerce accounts and call centre records rarely resolve to the same person, so repeat purchase, lifetime value and even basic frequency are understated, and retention activity targets a partial and biased view of the customer base.
04
Inventory visibility doesn't match reality
Online availability, store stock and delivery promises are often generated from different systems on different cadences, producing lost sales from false out-of-stocks and disappointed customers from false in-stocks.
05
Local discovery is under-invested relative to its influence
Store pages, Google Business Profiles, local inventory feeds and local search are treated as an operational afterthought rather than a demand channel, even where they materially shape footfall and call volume.
06
Store and ecommerce P&Ls compete for the same budget and stock
Promotional calendars, stock allocation and marketing spend are negotiated between formats as a zero-sum contest, rather than planned against where the incremental customer actually comes from.
07
Growth plateaus once easy channel gains are exhausted
Once each channel has been optimised in isolation, the remaining growth sits in the overlaps — cross-channel repeat purchase, assisted conversion, local capture — which nobody is set up to pursue because no team is measured on them.
03 — Economics
The numbers leadership should be able to see
Not a reporting wish list. These are the figures that decide whether more investment is a good idea, and the cuts that make them meaningful.
| Metric | What it tells you | How we read it |
|---|---|---|
| Identified sales rate | The share of total transactions (store and online) that can be matched to a known customer.Low or static rates mean retention and CRM decisions are being made on a minority, biased sample of customers. | Low or static rates mean retention and CRM decisions are being made on a minority, biased sample of customers. |
| Total customer value (blended) | Revenue per customer across every channel they use, not per channel account.Compare against channel-reported CLV, which typically fragments the same customer into several smaller ones. | Compare against channel-reported CLV, which typically fragments the same customer into several smaller ones. |
| Sales per square foot / per store | Whether physical footprint is earning its space, and how it moves alongside digital investment nearby.Read alongside catchment digital spend and local search visibility, not in isolation. | Read alongside catchment digital spend and local search visibility, not in isolation. |
| Digitally-influenced store revenue | Store sales preceded by a locator visit, product research session, or online stock check.Depends on consistent tracking of pre-visit digital touchpoints; without it this is usually estimated, not measured. | Depends on consistent tracking of pre-visit digital touchpoints; without it this is usually estimated, not measured. |
| Click & collect and reserve conversion | Whether online-to-store handoffs are actually converting or leaking at pickup.Cut by store, since fulfilment reliability varies far more than the aggregate number suggests. | Cut by store, since fulfilment reliability varies far more than the aggregate number suggests. |
| Assisted / call centre conversion rate | The share of calls or showroom visits that convert, and their attributed revenue.Rarely fed back into channel attribution models, which understates the marketing that generated the enquiry. | Rarely fed back into channel attribution models, which understates the marketing that generated the enquiry. |
| Geo uplift from local marketing and store openings | The incremental effect of local activity on nearby digital and store demand.Requires geographic holdouts or store-opening natural experiments; platform reporting alone won't show this. | Requires geographic holdouts or store-opening natural experiments; platform reporting alone won't show this. |
| Stock availability accuracy (online vs actual) | How often published online or store availability matches what's actually on the shelf.A hidden driver of lost sales and returns that rarely appears in standard commercial reporting. | A hidden driver of lost sales and returns that rarely appears in standard commercial reporting. |
04 — False positives
What can look healthy but isn't
- Looks fineEcommerce is growing while store revenue declines, so digital investment is clearly working
- Some of that ecommerce growth is likely to be store revenue displaced by online research and click & collect rather than net new demand, and some store decline may be caused by underinvestment in the very digital assets that used to drive footfall.
- Looks fineStore locator and 'near me' traffic is small, so it's not worth optimising
- Locator sessions are a leading indicator that correlates with store visits and calls far more strongly than their raw volume suggests; the small number of sessions can precede a disproportionate share of high-intent physical visits.
- Looks fineLoyalty membership is high, so retention is under control
- Membership counts often include customers whose store and online identities were never merged, meaning the loyalty base looks larger and more active than the set of customers actually being retained and communicated with coherently.
- Looks fineA promotion drove a strong sales week across the estate
- Without a control group of stores or regions held out from the promotion, it's difficult to separate genuine uplift from pulled-forward demand, seasonality, or a competitor's simultaneous closure or stock-out.
05 — Flagship
The Growth Diagnostic in this model
The Growth Diagnostic in this model spends proportionally more time on how demand and data move between channels than on any single channel's internal optimisation, because that is where the biggest and least-examined value usually sits.
- 01Demand/MarketHow total demand splits across online, store, call centre and distributor, by geography, and how that split is actually measured rather than assumed from channel-reported sales.
- 02DiscoveryHow customers find and research the brand locally — search, store pages, Google Business Profile, reviews — and how that discovery activity relates to footfall, calls and appointments.
- 03AcquisitionWhere marketing spend sits relative to where customers are actually acquired, including the share of acquisition that happens through assisted and offline channels but is credited elsewhere or nowhere.
- 04ConversionFriction in the cross-channel journey — stock visibility, pricing consistency, click & collect handoffs, appointment booking — and how much of it is silently costing sales.
- 05RetentionWhether loyalty and CRM activity reaches the same customer consistently across channels, and how repeat purchase and total customer value actually behave once identity is resolved.
- 06MeasurementWhether attribution, geo testing and blended reporting exist in a form leadership can act on, or whether each channel is still marking its own homework.
- 07CapabilityWhether the team, agency and data structure around ecommerce, retail, marketing and CRM can actually execute a cross-channel plan, or whether ownership gaps and incentive conflicts will quietly undo it.
06 — Growth problems
Start from the problem you recognise
Each of these is written for this business model specifically: the symptoms, the likely causes, the numbers we would look at, and what tends to mislead.
Digital's influence on store sales isn't being measured
Search, store locator and calls are shaping footfall and phone enquiries, but digital only gets credited for sales it closes directly.
Customers hit friction moving between online and in-store
Stock, pricing, promotions and account details don't match between online and store, and customers absorb the cost of that mismatch.
Store and ecommerce are competing instead of compounding
Separate P&Ls, KPIs and stock pools put store and ecommerce teams in competition for the same customer.
Local search and discovery aren't converting into store demand
Store pages, local listings and local search are under-managed relative to how much footfall and call demand they influence.
Stock visibility problems are costing sales across channels
Online availability, store stock and delivery promises frequently disagree, and each mismatch costs a sale or a customer's trust.
Customer data is fragmented across store and digital systems
POS, loyalty, ecommerce accounts and CRM rarely resolve to the same customer, so retention and value metrics understate reality.
Growth has plateaued once single-channel gains are exhausted
Each channel has been optimised individually, but total growth has flattened because nobody owns the space between them.
Loyalty and retention don't hold together across channels
Loyalty and CRM activity often only reaches a partial, digitally-biased view of the customer base, weakening retention.
Digital investment can't be justified against total business revenue
Digital marketing's platform-reported return understates its real effect once assisted sales and halo effects are included.
No one clearly owns cross-channel decisions
Ecommerce, retail, marketing, CRM and agencies each hold a piece of the customer relationship, but no one owns the whole.
Questions we get asked in this model
- We don't have unified customer data across store and online — can you still run this?
- Yes. Most businesses in this position start without it. Part of the diagnostic is establishing how far identity can realistically be resolved with your current systems, and what a pragmatic near-term improvement looks like, rather than assuming a full customer data platform is the first step.
- Is this only relevant if we have a large store estate?
- No. The same dynamics apply to a handful of showrooms, a call centre, or a network of concessions and distributors — anywhere a customer can move between an assisted or physical channel and digital before buying.
- Do you need access to store-level POS and CRM data?
- Ideally yes, at least at a summary level, since store-by-store variation is usually where the useful findings sit. Where that access isn't available quickly, we scope the diagnostic around what can be analysed credibly with what exists.
- Who from our business needs to be involved?
- Typically ecommerce, retail or store operations, marketing, and whoever owns CRM or loyalty, plus finance if store and digital P&Ls are reported separately. The friction between these teams is often as informative as the data itself.
Also relevant
Working through an agency?
- We provide the senior strategy and commercial layer behind agency delivery, white-label or co-branded.
- Non-solicitation by default: your client relationship stays yours.
- Useful when a client needs a diagnostic view that sits above channel delivery.
Understand what's actually driving growth across your channels
A Growth Diagnostic gives you a blended, evidence-based view of where demand is created, where it converts, and where investment and operating structure are working against each other.