Retail Analysis
It’s For You-Hoo
Inevitably, retail analysis is for retailers – big or small, so long as they’ve got a retail outlet of some kind. But retail analysis is also for suppliers, distributors, FMCG manufacturers and anyone else selling through retail channels. Add to that ad agencies wanting well-targeted product launches and cost-effective promotions, and public sector bodies needing to look at service provision in new ways, and Retail Analysis has something for almost everyone.
Catchment Area Reports & Maps
“Check it out before signing the lease” as the Board would say! SPA’s catchment reports are designed to tell you what you need to know. For your chosen area (e.g. 0.5 miles, 15 mins drivetime etc.) around the branch Postcode, you can have any of the following:
Census demographics – a profile of the population living in the store catchment
MOSAIC mix – population, adults or households in the same area split by MOSAIC Types/Groups
Demographic Map – showing a Census variable by Output Area, or MOSAIC by Postcode
Local Retail Profile – Retail Locations data by retail sector – even who’s there if that matters
Workplace & Workforce Data – Market Location data by SIC and size band
Competition report or map – showing who’s there, and where, in relation to your site.
Local Area Customer Potential – bespoke model estimates from your own customer profile.
See Where Can I Find More People Like My Customers? (Additional modelling cost.)
See Where Can I Find More People Like My Customers? (Additional modelling cost.)
SPA produces bespoke site dossiers for a number of clients – particularly pub chains! For each site identified to us, we produce a standard “pack” of reports and maps agreed with our client – e.g. a MOSAIC catchment area map, a tailored catchment demographics report, and perhaps a competitor proximity analysis and map.
New Branch Potential Analysis
What if you don’t even know where to start looking for new branches, or more distributors?
No problem. We can get the computer to rove round Britain trying out a new branch in each Postcode Sector – calculating how much customer potential it grabs, and whether it’s just taken off your existing outlets. We can then give you a ranked branch potential report listing the best potential new store locations (after removing neighbours providing duplicate coverage of the same catchment areas).
Of course, the computer needs to know what to look for – what makes for lots of customers and what doesn’t. Where possible we produce a MOSAIC profile of your existing customers, and use that to build a MOSAIC customer potential model. In its tour of Britain, the computer would then be looking for areas rich in the MOSAICs that provide you with the most customers – and would avoid everything else.
Even if you don’t have Postcoded customer data for us to profile, there are still options:
A survey to collect customer postcodes – see Your Survey
A profile of your store catchments – the more you have the better
A profile of your retail sales – the only option for many selling via retail outlets/stockists
Develop a targeting plan – brief SPA to identify the MOSAICs you want to target; this plan can then be used (instead of a customer profile) to build your potential model
Customer Catchment Analysis
Using their Postcodes, customers can be mapped in two ways:
Dot Maps – one dot per Postcode, perhaps colour-coded by customer type, product purchased
Shaded Maps – better for showing the concentration of customers v population. The heavier the shading, the higher is the proportion of the population that are customers.
Shaded customer penetration maps bring out areas of relative strength/weakness. So they’re good for defining primary and secondary store catchment areas, for assessing the effect of a competitor outlet on your market share, and for deciding where to promote your services.
In building a MOSAIC customer potential model, it is invaluable to know one of two things:
EITHER: How average penetration rates change with increasing drivetime or distance from the store. A shaded customer penetration map shows this information for one branch.
OR: On average, how far customers typically travel – or for how long they drive – to the store.
Simple analysis customer analysis gives us this key “distance decay” parameter, so helping make our customer potential models more realistic.
Competitor Analysis
Competitor Intelligence speaks for itself! All we need are the addresses of your outlets. We’ll source lists of your competitors’ outlets – and give you two types of report:
Proximity analysis: how many – and which – outlets have 1, 2, 3+ competitors on the doorstep? This helps identify stores which are more/less vulnerable to competitor price cutting, and stores which need marketing support to help face competitive pressures.
Positioning analysis: based on its catchment demographics, which market segment is each branch best placed to address? Are neighbouring, apparently competing stores really in the same parts of the market? Results have implications at both the strategic and tactical levels.
Analysis keeps ahead of the pack with insight into how they’re positioned and what you can do about them.
Distribution Check
Selling too little in some areas = missed opportunities.
Trying to squeeze too much from others = diminishing returns.
This is true for salesforces, and for retail distribution networks. If you’re putting too few sales reps or appointing too few stockists in the East of England and have too many in the North West, you’re missing out. SPA’s Distribution Check compares the sales resources you have allocated and sales volume you’re achieving, with the size of the available market in each local area. Most clients have no data on the market size in each area. Many have Postcoded customer data, which we can use to build good model estimates. Failing that, we can source third party information – e.g. market research or lifestyle data. SPA’s Distribution Check helps you match your sales effort to the size of the potential market – maximising your returns and minimising waste.
Segmentation
SPA has special expertise in Retail Segmentation – classifying retail outlet of all kinds into types for use in target marketing. You can then design specific promotions or other activity for each type, measure your market share by segment, or even assess your need for repositioning.
A Simple Example. We took basic geodemographic data for 374 supermarket branches and used cluster analysis to classify them into four types:
Bargain Basement Families [red]- concentrated in Northern England & Scotland
Mid Market Mums [orange]- particularly Midlands & South West
Active Affluent Kids [green]- especially Midlands and Mid South (not London!)
Upscale Urban Couples [blue] – over-represented in South and Midlands
Clearly the four segments represent contrasted market opportunities. Almost whatever the product, you wouldn’t not expect the same level of sales in all four environments. This simple fact can help us to improve the cost-effectiveness of our promotions and target all kinds of activity more appropriately.
Similar – or totally different – segmentations can be produced for almost any specific purpose or target. Once we’ve classified your outlets, you can use the classification to decide which promotion they get, which are suitable for the product launch, and where to roll out the Back2Basics range.
If you’re into Retail Segmentation, you’ll love SPA’s award-winning Segmentz system. It’s a simple idea: just classify all retail outlets on the same 4 dimensions. This gave us a standard retail segmentation covering all the branches of all Britain’s retail multiples – from banks and burgers joints to coffee shops and convenience stores, from fashion outlets and filling stations to sports shops and supermarkets. Using Segmentz, it is easy to sum up a single site objectively, or to benchmark a whole portfolio of sites –a pub estate, or a chain of High Street shops – and to compare them with your own branch network. Retailers using Segmentz can be more systematic in site selection, merchandising, and targeting promotions. Distributors & FMCG manufacturers using Segmentz can track their sales more effectively, and understand which outlet types are better for particular products or product portfolios, and which respond best to specific styles of promotion. Contact Us to request more information or to tell us why you’re interested in retail segmentation.
Turnover Prediction
SPA also builds computer models – using Multiple Regression, Neural Networks etc. – to predict the sales turnover of shops, pubs or other retail outlets. We predict the relative performance of outlets in different locations, not the performance at different points in time. Predicting outlet turnover is a big job. You need lots of branches (100+; ideally more), with data on the same basis for all of them.
Though you probably won’t have all the data, items of interest are Postcode, size, floorspace, space allocation, staffing, staff training, opening hours, visibility, appearance, lighting, site type, parking, neighbours, etc. SPA also attaches additional catchment demographics using the branch Postcode. All this data is then poured into the computer along with the latest sales figures. Finally, the computer produces the regression equation – a formula expressing outlet sales as a function of other input variables.
Once the model is finished, you can use it to predict the turnover of new stores before they open – based on the planned floorspace etc. and taking into account the local market demographics derived from the planned store’s Postcode. This means you can do 'what if' experiments – assessing the effect of a bigger store, putting the store in another town, or branding it differently. Turnover models can also help you set more realistic targets for your existing sites and so to identify under-performers.