Range Review Preparation: The Data Pack UK FMCG Brands Need Before a Buyer Meeting

You've got the meeting. Now the real work starts.

Most brands spend two weeks preparing a slide deck. Most buyers decide in the first five minutes whether the brand sitting across from them actually understands the category, or is wasting their time.

The difference isn't how polished your presentation looks. It isn't your brand story. It's data. Specifically: do you have the right data, organised the right way, proving the right things - before you walk in the door?

This guide answers that question in full. It covers every data source, every metric, and every analytical lens you need to build a buyer data pack that earns the next step, whether that's a new listing, a range expansion, a distribution defence, or a joint business plan review. The same six data layers apply in every case.

We've written this for mid-market UK FMCG brands selling through the major grocery retailers. The brands for whom a range review isn't a routine exercise, it's a commercial decision that can move annual revenue in either direction.

What This Guide Covers

• Why range reviews in 2026 are harder to navigate than ever before
• What buyer data systems already know about your brand
• The six data layers every strong pack must include
• Where to source each type of data
• The most common preparation mistakes, and how to fix them
• A retailer-by-retailer breakdown of what changes across Tesco, Sainsbury's, Asda, Ocado, and Waitrose

1. Why Range Reviews Are Harder Than They've Ever Been

Let's start with the environment. Understanding what's happening in UK grocery right now explains why brands that don't prepare properly are walking into a fundamentally different kind of meeting than they were three years ago.

UK grocery in 2026 is structurally tighter than at any point in recent memory. Three forces are converging on every buyer meeting simultaneously.

Private label has crossed 50% unit share. According to Circana's April 2026 analysis, own-brand products now account for 52% of UK grocery unit sales, a record high. Every percentage point of shelf space that private label gains comes from somewhere. That somewhere is usually a mid-market brand that couldn't make the numbers stack up in the last range review.

Buyers are under structural margin pressure. McKinsey's State of Grocery Europe 2026 report describes this moment as "the most decisive that European grocery has seen in a decade," as cost pressure, regulation, and digital monetisation converge at the same time. A buyer defending their category's margin has every incentive to rationalise slow-moving or underperforming branded lines.

Tesco's "Fit for Growth" reset changed the standard for everyone. Tesco's macro-level range review, described by The Grocer as the biggest since Dave Lewis' 2015 Project Reset cull, wasn't just a Tesco event. It signalled to every major retailer that full-estate range rationalisation was back on the table. The ripple effect across Sainsbury's, Asda, and Ocado is real, and buyers across the board are being asked harder questions about every listing they defend.

None of this is meant to be daunting. It's meant to be useful. Understanding what a buyer in 2026 actually needs to see is the first step to showing up with it.

A range review is not a pitch. It's a decision forum. The buyer already has all the retailer-side data. Your job is to bring the brand-side data they don't have, organised in a way that makes saying yes the obvious move.

2. What a Buyer Already Sees Before You Walk In

The Retailer Data Advantage

Before you can build your data pack, you need to understand what's already sitting on the buyer's desk.

Every major UK grocery retailer runs sophisticated supplier data platforms. These aren't just reporting portals, they're full commercial intelligence systems. Tesco uses Dunnhumby-powered analytics through its supplier-facing tools. Sainsbury's runs its Insights Platform (SIP) through the Together With / SupplyHub portal, operated by Circana since 2024, giving subscribers three full years of transactional and customer data. Asda's supplier portal (the ADR system) provides weekly sales and distribution reporting, and Ocado suppliers access performance data through a separate commercial portal.

What this means in practice: the buyer knows your rate of sale. They also know your distribution trend, your promotional uplift, your availability rate, your return rate, and how you perform relative to category benchmarks, often more precisely than you do.

The Asymmetry Most Brands Underestimate

This creates a gap that commercial teams consistently miss. Walking into a range review with data the buyer already has, and worse, presenting it in a frame that doesn't match theirs, signals that you're working from a different picture of reality. That's a credibility problem before the conversation has properly started.

Your data pack needs to do two things at once. First, confirm that you're working from the same data the buyer has. Then, add the dimensions they don't have, such as shopper context, competitive framing, forward-looking projections, and the story that turns raw numbers into a clear decision.

"Buyers want clarity fast, then evidence. Do not bury the ask. Do not save numbers for the end."

• Grocery Impact, Former Supermarket Buyers, January 2026

3. The Six Data Layers Every Range Review Pack Must Include

There's no single correct format for a buyer data pack, as it varies by retailer, category, and commercial situation. But every strong pack, regardless of where it's going or what it's asking for, contains the same six layers of data. Miss any one of them and you're handing the buyer a reason to stay on the fence.

Layer 1: Rate of Sale (ROS)

Rate of sale is the metric buyers care about most, not total sales value, but rate of sale per store per week. It's the purest signal of how efficiently your product generates revenue on shelf, and it's how buyers compare SKUs within a category regardless of how wide their distribution is.

Your ROS data needs to cover:

• Base ROS (excluding promotional weeks)
• Promotional ROS (uplift factor and post-promotion normalisation)
• ROS trajectory over the past 13 and 52 weeks (trending up, flat, or declining)
• ROS versus category average (your benchmark position)
• ROS by store format (for example, Extra versus Express for Tesco, superstore versus convenience)

The most common format mistake is presenting total weekly sales rather than per-store ROS. A brand with 800 stores doing £16,000 per week doesn't look as compelling as a brand with 400 stores doing £40 per store per week, but the second brand has a far stronger argument for distribution growth.

Example ROS framing for a buyer pack:

Base ROS (52-week avg):        £38.20 per store per week
Category average:              £31.50 per store per week
Your index vs category:        121 (21% above average)
Promotional ROS:               £61.40 per store per week (61% uplift)
Post-promo ROS trend:          Returns to £38.80 within 4 weeks (minimal dip)
13-week trend:                 +7.4% (accelerating)

That's a compelling data argument in six lines. Most brands take twelve slides to say less.

Layer 2: Distribution Data

Distribution tells the buyer where your product is and, critically, where it isn't. Two types of distribution data matter here.

Numeric distribution is the percentage of stores that carry your product. If you're in 600 of 2,900 Tesco stores, your numeric distribution is 20.7%.

Weighted distribution is the percentage of category sales volume generated by the stores carrying your product. A brand in 20% of stores that represent 35% of category volume has a weighted distribution of 35%. This is a more useful metric for ranges that are weighted towards large formats.

The distribution gap analysis is where most brands leave money on the table. A distribution gap is the difference between where you're listed today and where your rate of sale performance justifies listing.

Present this as commercial opportunity, not complaint. "Our ROS in listed stores outperforms the category leader. The unlisted 27% of Tesco stores represent approximately £X of incremental weekly sales at current ROS. Here's our plan to close it."

Layer 3: On-Shelf Availability (OSA)

This is the data layer most brands walk into a range review without. And it's increasingly the one that matters most.

The UK grocery average on-shelf availability rate is 89.7% (Retail Economics/DHL, 2026). That means roughly one in ten items a shopper looks for isn't on the shelf when they want it. For FMCG suppliers, avoidable stockout loss sits at around 5-8% of addressable sales, year in, year out, for the typical mid-market brand.

Why does this matter in a range review?

First, availability failures suppress your reported ROS. A product that sells out by Wednesday in 30% of stores shows a lower average ROS than its true demand would generate. If you walk into a range review with an OSA problem you haven't surfaced, you're defending a depressed number.

Second, a buyer who can see availability data through the retailer portal already knows if your product has a consistent stockout pattern. Not addressing it proactively is far worse than addressing it with a clear remediation plan.

What to include in your OSA section:

• Your 13-week average OSA rate by retailer
• Store-level distribution of availability failures (clustered by region, format, or day of week?)
• Root cause identification (phantom inventory, shelf depth miscalibration, replenishment lag, distributor compliance)
• Remediation plan with timeline

OSA Data Summary (Tesco, 13-week period):

Average OSA:           91.4%
Target (world-class):  96%+
Gap to target:         4.6pp
At-risk sales:         ~£X per week at current ROS
Primary failure type:  Replenishment lag on Thursdays in 
                       convenience formats (83% of incidents)
Remediation:           Frequency uplift in top 40 failing stores,
                       supported by field rep visit programme

Proactively surfacing your own availability data, including the gap, and arriving with a fix demonstrates operational credibility. Buyers who spot the problem themselves and you haven't mentioned it will draw their own conclusions.

4. Layer 4: The Category Story - Why Your Brand Makes the Shelf Better

Everything up to this point has been about your performance. This layer is about the category.

The category story is not your brand story. Experienced buyers are clear on this: "Leave the founder journey in the appendix. Show me why your brand improves the shelf for the shopper."

There are four components to a strong category story.

Shopper penetration. How many UK households buy your category versus how many buy your brand? The gap is your penetration opportunity. Panel data from Kantar or NIQ is the standard source here. Consumer Reach Points (CRPs), the Kantar metric calculated as households multiplied by purchase frequency, quantifies your brand's footprint against the category's total addressable consumer base.

Incrementality versus substitution. Does your product bring new shoppers into the category, or does it cannibalise existing ones? Buyers want incrementality. If you can show that 60% of your buyers don't regularly purchase the leading brand in the category, you're demonstrably adding rather than stealing.

Basket association. What else do shoppers buy alongside your product? This is especially powerful for retailers with strong loyalty card data, such as Tesco Clubcard and Nectar. A product that consistently appears in baskets with high-margin categories, or that associates strongly with frequent shoppers, carries a different commercial weight than one that exists in isolation.

Gap identification. What need state does the category currently fail to serve? Frame it in shopper terms: "There is no product currently on the Tesco shelf that addresses [shopper occasion or need]. Our brand addresses it. Here's the sales evidence from [reference retailer or market]."

"The category story is the logic that makes the buyer safe to say yes."

• Grocery Impact, 2026

5. Layer 5: Financials - The Numbers That Tell the Buyer They Can Afford to Say Yes

A buyer can like your brand and still say no. The commercial case has to work independently of goodwill.

The financial layer of your data pack needs to cover six specific areas.

Buyer margin (POR). Your product's percentage of retail is the buyer's gross margin on each unit. Know your current POR, know the category average POR, and be ready to explain how you sit relative to both. If you're below the category average, have a plan to address it. If you're above, make that a clear strength.

Trade funding model. How much do you invest in promotional activity, and what return does it generate? The standard frame covers promo depth (percentage discount), frequency (weeks per year), and the total trade investment pot. Buyers want to understand your promotional architecture, whether you're a high-frequency, shallow-discount brand or a deep, occasional promoter. Both have legitimate category roles, but you need to articulate yours deliberately.

Promotional ROI. What does a promoted week actually deliver? Look at rate of sale during promotion versus baseline, plus the post-promo return trajectory. A brand that delivers 60% promotional uplift and returns to a stable base within two to three weeks is demonstrably stronger than one that delivers 80% uplift and then falls below baseline for six weeks.

Case size and depot compliance. Operational friction matters to buyers. Confirm your case sizes, pallet configurations, minimum order quantities, and your compliance record with retailer distribution centres. A history of supplier delivery issues is a risk factor that buyers factor into listing decisions, particularly right now.

Cost price trajectory. If you've raised prices in the past 12 to 24 months, be ready to explain the cost drivers and show where they've stabilised. Buyers know the commodities market well. They'll know whether your cost price increases were justified, and trying to obscure this works against you.

Supply chain resilience credentials. Post-COVID, buyers weight supply chain confidence more heavily than before. BRCGS certification, dual-sourcing evidence, lead time guarantees, and contingency stock capacity all belong in this section.

Financial Summary Frame (one page):

                          Your Brand    Category Avg    Index
Buyer margin (POR):        38.2%          36.5%          105
Promo frequency:           8 wks/yr       11 wks/yr      --
Promo depth:               20%            22%            --  
Promo uplift (ROS):        +58%           +43%           135
Post-promo retention:      97.3%          91.0%          107
Trade investment (annual): £[X]
Estimated category value   £[X]
generated by brand:

Never present financials without a commercial implication. The number is never the point. The decision it supports is the point.

6. Layer 6: The Forward Plan - What Happens After They Say Yes

A range review isn't just about what you've done. It's equally about what you're going to do.

The forward plan is where many brand teams are weakest. They've done the hard work on historical data and then produce a vague "we plan to grow" slide for the final section. That's not enough. A buyer signing off a listing or distribution extension needs to see a concrete plan with enough specificity to hold you accountable.

Here's what to include.

NPD pipeline (if applicable). New product development news is a powerful listing argument. A buyer who lists your core SKU gets a first look at your innovation, which is a commercial incentive in itself. If you have NPD in the pipeline, frame its role in the category: what gap does it address, what is the ROS forecast, and what evidence from test markets supports it?

Activation plan. What are you doing to drive consumer demand during the listing period? This covers digital media investment (including retail media - Dunnhumby, Nectar360, LS Eleven for Asda), in-store POS, sampling, and social reach. Buyers want to see that you're pulling consumers to the shelf, not relying on the listing alone.

Ranging recommendation. Don't wait for the buyer to tell you what they should range. Come in with your recommendation, show the evidence, present the SKU architecture, and propose the shelf allocation. Buyers who receive a well-reasoned ranging proposal will engage with it far more productively than those who face a brand waiting for direction.

Volume forecast. Commit to numbers. If you're asking for distribution expansion into 200 additional Tesco stores, show the expected weekly sales revenue, the buyer margin in absolute £, and the timeline for reaching a steady-state rate of sale. Make the assumptions explicit.

JBP data alignment. If you're in a joint business plan review or building towards one, this section connects your forward plan to shared KPIs. Come in with your proposed JBP metrics pre-built. Don't wait to be handed a template.

7. Where to Get the Data

Knowing what data you need is one thing. Knowing where it lives is another. Here's how each data type maps to its source for UK FMCG brands.

Retailer Portal Data (Start Here)

Every major retailer gives suppliers access to their own sales data through a portal. These portals are the raw material for any buyer pack, and each one works differently.

• Tesco: Tesco Connect (supply chain) and Dunnhumby-powered reporting tools. Weekly EPOS, distribution, and availability data at store level.
• Sainsbury's: SupplyHub platform (Circana-operated since 2024). Three years of full transactional data, including customer-level metrics via the Sainsbury's Insights Platform (SIP). Subscription-based with tiered packages.
• Asda: Asda Data and Reporting (ADR) via the Asda Supplier Portal. Weekly sales and distribution reporting. The system migrated from the legacy Retail Link, so confirm your ADR connection is live before pulling data.
• Ocado: Ocado partner portal. Particularly strong for repeat purchase rate and basket association data, given the Ocado customer profile.
• Waitrose: Waitrose Partner portal. Store-level performance with category context.

The challenge is that each portal uses different metrics, different time periods, and different hierarchy levels. Combining data from Tesco Connect and Sainsbury's SupplyHub into a single coherent view requires significant manual work, or a connected data layer that does it automatically.

Third-Party Panel and Market Data

Retailer data tells you what happened in that retailer. Panel data tells you what's happening with the shopper regardless of where they buy.

Your Own Internal Data

Don't underestimate what you already have in-house. Your NAM's weekly sales reports, your Cin7 or NetSuite order data, your 3PL delivery records, your field team's in-store audit reports, all of this contains signals that external panel data doesn't capture.

Specifically:

• Order data versus sell-through data: the gap between what you ship and what scans at the till is your availability and shrinkage signal
• Regional delivery records: if your 3PL has DC compliance logs, use them to pre-empt availability conversations
• Field audit data: if your team visits stores, you have visibility of execution compliance that the buyer doesn't

The practical challenge for most mid-market brands is that this data sits in at least four separate systems with no single view that stitches it together.

8. The Most Common Data Pack Mistakes, and How to Fix Them

These mistakes come up consistently across mid-market brands at every stage of range review preparation. The good news is that every one of them is fixable in the two weeks before your meeting.

Mistake 1: Presenting total sales instead of ROS

Total sales is not a useful number without context. A product doing £80,000 per month across 2,000 stores is performing worse than one doing £30,000 per month across 300 stores. Always convert to per-store, per-week ROS before presenting anything to a buyer.

Mistake 2: Using national averages to hide regional problems

If your product is at 89% availability nationally but Scotland is at 72%, the national average is hiding a problem the buyer can already see in their portal. Surface regional issues before they do, with a plan to fix them. Tesco's April 2026 change to report Scotland availability separately has made this particularly relevant, as regional availability is now explicitly visible in a way it wasn't before.

Mistake 3: No comparative benchmark

Your ROS in isolation is meaningless. Your ROS at 121% of the category benchmark, however, is a clear listing argument. Every metric in your pack needs a benchmark, whether category average, leading brand, or prior year, that contextualises your number.

Mistake 4: Confusing "in stock" with "available to buy"

Phantom inventory refers to products that appear as "in stock" in the system because they're in the backroom or allocated to a different location. It's a widespread and underreported problem. A product showing 94% in-stock in a retailer's system can have a genuine shopper-facing availability of 86%. If you're not accounting for phantom inventory in your OSA reporting, you're presenting a figure that doesn't reflect what shoppers actually experience.

Mistake 5: Presenting data that hasn't been quality-checked

A data error in a buyer meeting, whether a formula mistake, a percentage that doesn't add up, or a prior-year figure that contradicts the retailer's own system, destroys credibility immediately. Every number needs to be sourced, cross-checked against the retailer portal, and signed off by someone who wasn't the person who built the pack.

Mistake 6: No forward-looking data at all

Historical data explains what happened. Buyers make listing decisions based on what will happen. Your pack needs at least one section that converts historical performance into a forward-looking projection, with assumptions stated explicitly.

9. How to Structure the Pack

The structure of a buyer data pack matters as much as the content. Buyers who review multiple supplier packs in a category review cycle develop strong preferences for clarity and sequential logic.

Here's the structure that works consistently across Tesco, Sainsbury's, Asda, and Ocado range reviews for UK mid-market brands.

Section 1: The Headline (1 page)

One number, one insight, one ask. Not a brand story, not a trend overview. Start with the commercial outcome you're proposing: "We're proposing a 15% distribution extension across Tesco Extra stores. Here's why it works for the category and for your margin."

Section 2: Category Context (2–3 pages)

Where is the category going? What consumer trends are driving or threatening it? What gap on the shelf does your brand address? Use Mintel, Kantar, or IRI data, cited explicitly.

Section 3: Your Performance (3–4 pages)

ROS, distribution, OSA, promotional performance. All benchmarked. All trended across 13 and 52 weeks. No vanity metrics.

Section 4: Shopper Data (2–3 pages)

Penetration, incrementality, basket association. This is where Consumer Reach Points, Kantar panel data, and retailer loyalty card analysis live. Make the link between shopper behaviour and category value explicit.

Section 5: Commercial Summary (1–2 pages)

Buyer margin, promotional model, trade investment, supply chain credentials. Clean and simple.

Section 6: The Forward Plan (2–3 pages)

NPD pipeline, activation budget, volume forecast, JBP KPIs. Specific, committed, and with clear accountability.

Section 7: The Ask (1 page)

Return to the ask from Section 1. Re-confirm it in light of everything you've presented, and give the buyer a single clear decision to make.

Appendix: Supporting Data

Raw data tables, methodology notes, store-level breakdowns. Available if the buyer wants to go deeper, but not in the main pack.

Total pack length: 14–18 pages plus appendix. Send a one-page pre-read 24 hours before the meeting. Use the meeting to decide, not to discover.

10. What Changes by Retailer

The data pack framework above works across all major UK grocery retailers. That said, each retailer has specific emphases that a well-prepared brand will address directly.

Tesco

Tesco buyers work with Dunnhumby data constantly, so they are highly fluent with loyalty-level analytics and will push back on category claims that don't align with Clubcard cohort data. The Fit for Growth programme puts particular emphasis on health credentials, sustainability, and supply chain efficiency. If your product has HFSS implications, prepare your response before the meeting, because it will come up. Tesco's review cadence for most categories is annual, with mid-year check-ins, and the September-to-January window is when major range reset decisions typically land.

Sainsbury's

Sainsbury's buyers use the SIP extensively. If you have SIP access, use it, as presenting the buyer's own data back to them in a well-organised frame is a strong credibility signal. Nectar loyalty data is particularly powerful for incrementality arguments. Sainsbury's is also investing heavily in premium own-label (Taste the Difference), so any branded range review needs to address why your product justifies the premium tier against their own-brand equivalent.

Asda

Asda is in active commercial transformation under TDR Capital, and buyers are under pressure to deliver price-led positioning while managing range and margin. They are particularly receptive to clear price architecture arguments and promotional efficiency data. Asda's ADR system was fully rolled out in 2024, so make sure your data is pulled from ADR rather than the legacy Decision Support System to match what the buyer sees.

Ocado

Ocado is structurally different from the in-store retailers. Repeat purchase rate and basket affinity are the primary metrics, so a product that generates strong online repeat is a different listing argument than one that relies on impulse or secondary siting. With Ocado's same-day delivery expansion accelerating through 2026, replenishment windows have compressed, so supply chain reliability credentials carry extra weight here.

Waitrose

Waitrose buyers weight quality credentials, provenance, and premium positioning more heavily than other retailers. BRCGS A-grade certification, ethical sourcing, and clear quality differentiation from own-label are expected, not optional. The Waitrose buyer community is also tighter-knit than the big four, and word travels quickly about brands that underperform against their listing promises.

11. The Data Timeline: Building the Pack Without Burning Out Your Team

Range review preparation for a mid-market FMCG brand typically involves at least three team members - a NAM, a category manager, and a supply chain lead - working across four or five separate data systems. The timeline below assumes a six-week runway from confirmation of the review date.

Weeks 1–2: Data collection

Pull all available retailer portal data: EPOS, distribution, availability, and promotional performance. Simultaneously request any third-party panel data you have access to, and brief your field team to run in-store availability audits for the relevant category. Extract 13-week and 52-week sales and order fill rates from your ERP (Cin7, NetSuite, or equivalent), along with any 3PL compliance reports.

Week 3: Data QA and synthesis

Check every number against every source. Identify conflicts between your internal data and retailer portal data, and there will be some, so you need to understand why before the buyer asks. Convert all sales figures to per-store, per-week ROS and calculate benchmarks.

This is where most brand teams hit their biggest bottleneck. Without a connected data layer, Week 3 is often four days of spreadsheet work.

Week 4: Category story and commercial model

Build the category story using panel and market data. In parallel, run the financial modelling for your forward plan, covering volume forecast, margin model, and trade investment.

Week 5: Pack build and internal review

Draft the full pack in the agreed format. Run an internal review with the commercial director and supply chain lead, checking every claim against the source data. Then red-team the five most likely buyer objections.

Week 6: Pre-read, rehearsal, final prep

Finalise the pack and send the one-page pre-read 24 hours before the meeting. Rehearse the pitch, specifically the data sections, and prepare for questions about OSA, promotional efficiency, and forward pricing.

Range Review Preparation Timeline:

Week 1–2: Data collection from all sources
Week 3:   QA, synthesis, benchmark calculation
Week 4:   Category story, financial model
Week 5:   Pack build, internal review
Week 6:   Pre-read, rehearsal, buyer meeting
T+1 day:  Follow-up data pack (any parked questions)
T+5 days: Chase on next steps

12. How Data Preparation Connects to Your Ongoing Account Management

The Structural Problem Most Brands Share

A range review data pack is not a standalone event. It's the crystallisation of work that should be happening continuously throughout your account management.

Most mid-market FMCG brands share a structural problem: the data that goes into a range review pack is assembled once a year under time pressure, rather than being maintained as a continuously updated picture of account performance. The result is a commercial team that spends the six weeks before a review doing work that should already be done.

What Continuous Account Intelligence Looks Like

The brands that consistently win range reviews, and consistently earn distribution expansions rather than delistings, are the ones operating with what GrowSights calls a continuous account intelligence model. In practice, this means a live, connected picture of ROS, distribution, availability, and category performance that updates weekly and generates alerts when a metric starts moving in the wrong direction.

The practical difference is significant. When a brand operating this way walks into a range review, the data pack is mostly built. What would otherwise take six weeks of preparation takes six days of final assembly, because the commercial team has been watching the numbers move for 52 weeks. They know the story before they enter the room.

Three Practices That Close Most of the Gap

For brands not yet operating this way, three minimum practices make a big difference.

Weekly retailer portal download routine. Someone on the commercial team should download key EPOS and distribution data from each retailer portal every week, not when a range review appears on the calendar. This creates the trend data you need without the last-minute scramble.

Monthly OSA review. On-shelf availability should be reviewed monthly across every retailer where you have a significant listing. If you're not seeing your own availability data on a regular cadence, you'll find out about problems from the buyer rather than surfacing them yourself.

Quarterly performance benchmark update. Every quarter, update your benchmark table: your ROS versus category, your distribution versus the leading competitor, your OSA versus the retailer average. This keeps you calibrated and means you're never surprised by what the buyer presents back to you.

These three practices don't require enterprise analytics infrastructure. They require discipline and a clear internal owner.

Key Lessons for Retail Leaders

Lesson 1: The Buyer Already Has Your Data

The gap between what a buyer can see through Dunnhumby, SIP, or ADR and what most brands actually bring to a range review is significant, and it undermines brands that don't account for it. Your data pack's job is not to show the buyer numbers they don't have. It's to frame the numbers they already have in a story that leads to a decision in your favour.

Ask yourself: Does our pack add genuine insight to data the buyer already has? Or are we just reprinting our sales figures in a nicer format?

Lesson 2: Availability Is a Listing Argument, Not Just an Ops Problem

With £2.1 billion of UK grocery sales at risk annually from stock gaps, and the average UK on-shelf availability rate sitting at 89.7%, availability data belongs in your commercial pack, not siloed in supply chain. A brand that can show strong availability performance, explain its root cause analysis, and demonstrate a clear remediation plan is showing commercial maturity. One that ignores availability is leaving an obvious attack vector open.

Ask yourself: Do we know our actual OSA rate by retailer, by format, and by region? And if we have gaps, do we have a plan we can put in front of a buyer?

Lesson 3: Rate of Sale Beats Total Sales Every Time

Total revenue is a vanity metric in a range review. Per-store, per-week ROS is the signal that matters. A small brand with a high ROS in limited distribution has a compelling argument for expansion. A large brand with a declining ROS and heavy promotional dependency has a problem, however high its total revenue looks.

Ask yourself: Can we present our performance entirely in per-store, per-week ROS terms, including a benchmark against the category average and the leading competitor?

Lesson 4: Regional Data Matters More Than You Think

Tesco's April 2026 change to report Scotland availability separately from national figures made visible something that was always there: national averages systematically hide regional performance variance. A product at 88% OSA nationally may be at 71% in Scotland and 73% in Yorkshire. The buyer can now see that. You need to see it first.

Ask yourself: Do we have store-level or at minimum regional performance data for every major retailer? Or are we working from national aggregates that could be hiding serious problems?

Lesson 5: Private Label Pressure Makes the Category Argument Non-Negotiable

With own-label now at 52% of UK grocery unit volume and still growing, the "branded premium" argument is under more pressure than at any previous point. The brands that win range reviews in this environment are the ones that can prove their value in category terms: they drive penetration, generate incremental spend, and attract high-frequency shoppers. The brands that lose are still relying on brand heritage arguments that haven't been updated since 2019.

Ask yourself: How does our brand story land in a world where own-label is the majority? Are we articulating our category role in shopper terms, or leaning on heritage?

Frequently Asked Questions

What data does a buyer already have before a range review?

Buyers at major UK grocery retailers have access to sophisticated supplier data platforms, including Dunnhumby at Tesco, SIP via SupplyHub at Sainsbury's, ADR at Asda, and equivalent portals at Ocado and Waitrose. These give buyers access to your rate of sale, distribution trend, promotional uplift, availability rate, and category benchmarks, often in more detail than you have yourself. Your pack needs to start from the same data, then add the shopper context and forward-looking story they don't have.

What is the most important metric in a UK grocery range review?

Rate of sale per store per week is the metric buyers use most to evaluate performance and compare SKUs within a category. Total revenue figures are far less useful because they don't account for distribution breadth. A product with strong per-store ROS in limited distribution has a stronger argument for listing than a product with high total sales spread thinly across many stores.

How long should a buyer data pack be for a UK range review?

A well-structured range review data pack for a UK grocery retailer typically runs 14–18 pages plus a supporting appendix. The main pack should cover the headline ask, category context, performance data, shopper data, financials, and the forward plan. A one-page pre-read should be sent to the buyer 24 hours before the meeting.

When should range review preparation start?

Six weeks before the review date is the recommended runway for a mid-market FMCG brand. Weeks one and two are data collection; week three is QA and synthesis; week four is the category story and financial model; week five is the pack build and internal review; week six is final rehearsal and pre-read. Following up within 24 hours after the meeting with any parked data questions is equally important.

How do range review data requirements differ across Tesco, Sainsbury's, and Asda?

Tesco buyers are highly fluent with Dunnhumby loyalty analytics and prioritise health, sustainability, and supply chain efficiency under the Fit for Growth programme. Sainsbury's buyers use SIP extensively and are focused on premium positioning and Nectar loyalty incrementality. Asda buyers, operating under TDR Capital's price-led strategy, are most receptive to clear price architecture and promotional efficiency arguments. Each retailer warrants a tailored emphasis in your pack, even if the underlying data structure is the same.

Actionable Recommendations

For FMCG Brand Founders and Commercial Directors

• Establish a weekly retailer portal data download routine before your next range review is booked. Build the habit now, not under time pressure.
• Conduct an OSA audit across every major retailer in the next 30 days. Know your number before the buyer tells you theirs.
• Commission a category share of wallet analysis using Kantar or NIQ data that shows your brand's incrementality, not just its revenue.
• Check that your data is being pulled from current portal systems: Sainsbury's SupplyHub (not legacy), Asda ADR (not legacy Decision Support), Tesco Connect.
• Assign a specific owner for range review data preparation, not the NAM who is also running the meeting. QA requires fresh eyes.

For National Account Managers

• Convert your entire reporting language to per-store, per-week ROS from today. Practise presenting in this format until it becomes natural in the room.
• Prepare your regional distribution and availability breakdown before every buyer conversation, not just formal reviews. Buyers who hear about regional problems informally are far easier to manage than buyers who surface them at formal reviews.
• Build your objection response matrix before every range review. The five most common buyer objections, namely price, velocity risk, range space, operational risk, and private label cannibalisation, each have evidence-based responses. Write them down, source the data, and rehearse them.
• Follow up within 24 hours of any buyer meeting with a data pack addressing questions that were parked in the room.

For Category Managers and Supply Chain Leads

• Integrate OSA data into monthly commercial reporting, not annual. Monthly. This is the data that keeps brands on shelf and out of range review risk.
• Build the volume forecast model for the forward plan section before the six-week preparation window begins. It requires the most iterations and takes the longest to quality-check.
• Document your supply chain credentials proactively: BRCGS grade, delivery compliance rates by retailer and DC, lead time performance. This belongs in every range review pack.

Summary

Build a Data Pack That Gets the Decision

Range reviews are the moments that move revenue materially. A well-prepared brand walks in knowing its numbers, knowing the category's numbers, and knowing what question the buyer needs answered to say yes.

The problem for most mid-market UK FMCG brands is that the data they need is sitting in four different portals, two spreadsheets, a NAM's email, and a 3PL report, and nobody has stitched it together into a picture the buyer can engage with in 45 minutes.

GrowSights works with UK FMCG brands to build exactly this kind of connected account intelligence, pulling Tesco Connect, Sainsbury's SupplyHub, Asda ADR, and internal ERP data into a single live view, generating weekly availability alerts, and producing buyer-ready data packs that close the gap between fragmented data and confident commercial decisions.

If your next range review is on the calendar and your team is already in spreadsheet mode, it's worth talking before the pack is built, not after. We typically find something a brand didn't know about itself in the first week. Learn more about how we work with mid-market FMCG brands, or explore more of our retail intelligence thinking.

Start the conversation with GrowSights

Research sources:

• Retail Economics / DHL: The Availability Effect Report, 2026 - on-shelf availability, £2.1bn lost sales figure
• Circana: Private Label Unit Share Report, April 2026 - 52% UK own-label figure
• McKinsey: State of Grocery Retail Europe, 2026
• Grocery Impact (Joanna Walker, Jennifer Mazure): Nail the Buyer Meeting, January 2026
• The Grocer: Tesco Fit for Growth range review reporting, 2025
• Kantar / Worldpanel by Numerator: Brand Footprint methodology and Consumer Reach Points
• Nectar360: Sainsbury's Insights Platform documentation
• SKUtrak: Joint Business Planning analysis, November 2025
• GrowSights: On-Shelf Availability: The KPI Missing From Your NAM's Scorecard, 2026
• Pricer: UK On-Shelf Availability consumer research, 2024/2025

Published by GrowSights | Retail Intelligence and Growth Engineering | Point of View