Retail Data 101

Annual planning with retail data: a calendar for CPG teams

Annual planning for CPG teams works better on a calendar. A quarter-by-quarter guide to when retail data should feed each planning step.

Sep 19, 20264 min read

Retail Data 101

Questions to ask before trusting a retail statistic

Evaluating retail statistics starts with plain questions about source, sample, period and definitions. A checklist to use before repeating one.

Sep 18, 20264 min read

Retail Data 101

Competitive analysis with retail data, done responsibly

Competitive analysis with retail data should compare like with like and stay within ethical limits. How to do it fairly and use what you find.

Sep 14, 20264 min read

Retail Data 101

Trade area analysis: zip codes, density, and reach

Trade area analysis defines where a store's shoppers likely come from. How zip codes, density and reach work as tools, and where they fall short.

Sep 12, 20264 min read

Retail Data 101

Data storytelling: turning a chart into a decision

Data storytelling starts with the decision a chart should inform. How to build one clear point, add the right context, and present it well.

Sep 9, 20264 min read

Retail Data 101

Writing a data-backed retail case study that holds up

How to write a retail case study that holds up: a clear setup, a fair comparison, honest limits, and results a skeptical reader can check.

Sep 7, 20264 min read

Retail Data 101

Economic indicators and retail sales: what connects them

Economic indicators and retail sales: which public measures matter, how to line them up with POS data, and where the connection breaks down.

Sep 4, 20264 min read

Retail Data 101

Building a retail analytics team: roles and skills

Building a retail analytics team: the roles to hire first, the skills that matter beyond SQL, and how to set the team up to be useful.

Aug 29, 20264 min read

Retail Data 101

Data governance for CPG teams: who owns the numbers

Data governance for CPG teams: deciding who owns each number, who can change a definition, and how data gets used within its agreed limits.

Aug 28, 20264 min read

Retail Data 101

Data feeds: how retail data reaches your systems

Retail data feeds move scan data from stores to your systems. Common delivery methods, what to check when a file arrives, and questions to ask.

Aug 24, 20264 min read

Retail Data 101

Charts that tell the truth: visualizing retail data

Retail data visualization done honestly: axis choices, chart types that fit the question, and the common traps that make a small change look big.

Aug 22, 20264 min read

Retail Data 101

Tender mix data: what payment type can and can't tell you

Tender mix data shows how a store's sales split across cash, card and benefits. What it can tell you, what it can't, and how to use it responsibly.

Aug 8, 20264 min read

Retail Data 101

Store openings and closures: keeping a panel comparable

Store panel changes, like openings and closures, can make totals look like growth or decline. How same-store methods keep comparisons honest.

Aug 5, 20264 min read

Retail Data 101

Day-of-week and time-of-day patterns in store data

Time of day sales patterns need the right data grain. What day-of-week data shows, what hourly analysis requires, and common traps to avoid.

Aug 3, 20264 min read

Retail Data 101

Household essentials and the fill-in trip

Household essentials often sell on the fill-in trip, when something runs out at home. What that means for pack sizes, prices and reading the data.

Jul 29, 20264 min read

Retail Data 101

Regional preferences: reading local data without stereotyping

Reading regional preferences in retail data takes the right baseline and a check on store mix. A method that avoids stereotypes and weak stories.

Jul 25, 20264 min read

Retail Data 101

Immediate consumption categories in small-format retail

Immediate consumption products are bought to use right away. Which categories fit, where they sit in a small store, and how to read their sales.

Jul 24, 20264 min read

Retail Data 101

Shopping missions: stock-up, fill-in, immediate consumption

Shopping missions explain why a shopper walked in: to stock up, fill in, or buy something to use now. How each mission shows up in store data.

Jul 22, 20264 min read

Retail Data 101

Preparing an account review with retail data

How to prepare an account review with retail data: what the buyer needs first, which numbers to lead with, and how to present bad news.

Jul 17, 20264 min read

Retail Data 101

Line extensions: what to check before adding a flavor

A line extension can grow a brand or just split its sales. The scan data checks to run before adding a new flavor, size or variety to the shelf.

Jul 4, 20264 min read

Retail Data 101

Correlation vs. causation in retail data

Correlation vs causation in retail data: why two trends moving together prove little, and what it takes to show one thing caused another.

Jun 27, 20264 min read

Retail Data 101

Index numbers: comparing categories of very different sizes

Index numbers in retail put categories of very different sizes on one scale. How to build an index, pick a base period and avoid misreading it.

Jun 22, 20264 min read

Retail Data 101

Moving averages and smoothing in sales data

Moving average sales figures smooth out daily noise. How to pick a window, what smoothing hides, and when to look at the raw numbers instead.

Jun 20, 20264 min read

Retail Data 101

The 4-5-4 retail calendar, explained

The 4-5-4 calendar splits the retail year into 13-week quarters of four, five and four weeks. Learn how it works and how to compare periods.

Jun 17, 20264 min read

Retail Data 101

Calendar effects: why an extra weekend changes a month

Calendar effects in retail sales explained: how weekday counts, holidays and month length move totals, and how analysts adjust for them.

Jun 15, 20264 min read

Retail Data 101

Year-over-year vs. month-over-month: choosing the comparison

Year over year vs month over month: what each comparison measures, when each one misleads, and how to report both without confusing readers.

Jun 13, 20264 min read

Retail Data 101

Normalizing store data so comparisons are fair

Retail data normalization adjusts raw sales for store count, selling days and panel changes so comparisons between stores and periods are fair.

Jun 12, 20264 min read

Retail Data 101

What is a UPC, and why is it the unit of retail data?

UPC level data explained: what a Universal Product Code identifies, why analysts build retail reports on it, and where it needs extra care.

Jun 8, 20264 min read

Retail Data 101

The analyst in a commercial argument

Analysis enters rooms where people have positions. How to contribute without becoming an advocate or being ignored.

Jun 3, 20265 min read

Retail Data 101

Sizing a market from a sample

Market sizing multiplies a measured sample by an assumption. Where the assumptions live and how to bound the answer.

May 25, 20265 min read

Retail Data 101

Forward buying by the trade

Distributors and stores buy ahead of a price move. What that does to shipment data, to scan data, and to the weeks afterwards.

May 13, 20265 min read

Retail Data 101

When not to run the analysis

Some questions should not be answered with data, and some should not be asked at all. Recognising both before work starts.

May 11, 20265 min read

Retail Data 101

Questions to ask before commissioning research

Commissioned research is expensive and frequently answers a question nobody needed. The questions worth asking first.

May 8, 20265 min read

Retail Data 101

Visualising retail numbers without misleading anybody

Most chart problems in commercial analytics are honesty problems. The conventions that keep a retail chart readable and fair.

May 4, 20265 min read

Retail Data 101

Private label in the data

Private label is measured differently and behaves differently. What that does to share, to category totals, and to competitive analysis.

May 1, 20265 min read

Retail Data 101

Basket penetration and its limits

Penetration counts how many baskets contain an item. What it measures well, and the household question it cannot answer.

Apr 11, 20264 min read

Retail Data 101

Delisting and the tail: reading a decline

A declining item may be losing shoppers or losing shelf. The measures that tell them apart, and what a tail is actually worth.

Apr 8, 20265 min read

Retail Data 101

Year over year, sequential, or moving total: choosing a comparison

The comparison you choose determines what you see. Three standard options, what each answers, and when each misleads.

Mar 13, 20265 min read

Retail Data 101

Time series decomposition for retail sales

A sales series contains trend, season, calendar effects and noise. Separating them is what makes a movement interpretable.

Mar 9, 20265 min read

Retail Data 101

Feature and display: inferring support from data

Scan data shows what sold, not what the store did. What can and cannot be inferred about promotional support, and why it matters.

Mar 7, 20264 min read

Retail Data 101

What a product identifier actually identifies

A UPC identifies a package, not a product. What that distinction does to reporting, and when an item is not the item you think.

Feb 25, 20265 min read

All topics

Retail Data 101

Annual planning with retail data: a calendar for CPG teams

Questions to ask before trusting a retail statistic

Competitive analysis with retail data, done responsibly

Trade area analysis: zip codes, density, and reach

Data storytelling: turning a chart into a decision

Writing a data-backed retail case study that holds up

Economic indicators and retail sales: what connects them

Building a retail analytics team: roles and skills

Data governance for CPG teams: who owns the numbers

Data feeds: how retail data reaches your systems

Charts that tell the truth: visualizing retail data

Tender mix data: what payment type can and can't tell you

Store openings and closures: keeping a panel comparable

Day-of-week and time-of-day patterns in store data

Household essentials and the fill-in trip

Regional preferences: reading local data without stereotyping

Immediate consumption categories in small-format retail

Shopping missions: stock-up, fill-in, immediate consumption

Preparing an account review with retail data

Line extensions: what to check before adding a flavor

Correlation vs. causation in retail data

Index numbers: comparing categories of very different sizes

Moving averages and smoothing in sales data

The 4-5-4 retail calendar, explained

Calendar effects: why an extra weekend changes a month

Year-over-year vs. month-over-month: choosing the comparison

Normalizing store data so comparisons are fair

What is a UPC, and why is it the unit of retail data?

The analyst in a commercial argument

Sizing a market from a sample

Forward buying by the trade

When not to run the analysis

Questions to ask before commissioning research

Visualising retail numbers without misleading anybody

Private label in the data

Basket penetration and its limits

Delisting and the tail: reading a decline

Year over year, sequential, or moving total: choosing a comparison

Time series decomposition for retail sales

Feature and display: inferring support from data

What a product identifier actually identifies