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British Sugar become category captains

Everything worked great - everyone was pleased with the 3Dprints and the information that was generated from retail smart planograms.

The presentation went very well, Asda acknowledged the amount of work that had been done for the review and out of that have made Allinson category captains...........

Thank you for all your help.
Andrea - British Sugar PLC

 

A major UK confectionary manufacturer gains additional shelf space and improved layout

Using a combination of Named Account Data and the Retail Smart planogram software, our client services team helped a major UK Confectionary Manufacturer gain additional shelf space and improved layout in the Confectionary category.

The Manufacturer in question, who planned to launch a completely new pack design, required assistance in producing a business case to change the layout of the confectionary fixture within a major Retailer, which would incorporate its new style packs.

The existing planogram was generated in Retail Smart planogram software and with the use of Named Account Data, we were able to prove that the particular brand did not have the space it deserved, in its original form, compared to its sales. The competitor products that were over faced based on their sales were highlighted so the Retailer could clearly identify areas for improvement.

The submitted business case resulted in the Retailer generating a completely new layout by adjusting the facings of the bagged confectionary section and adding new mini shelves to the middle of the fixture to make sure that the “new look” brand received a fairer percentage share of space in accordance with its sales (the original brand had previously sat, below eye level, on a shelf below the hanging bagged confectionary).

The new layout was implemented in a set of trial stores, and the sales were tracked against stores of similar size which had the original layout.

The result was that sales for the “new look” product increased in both types of stores, however, the sales for those stores that implemented the new trail layout increased on average by 3% more that the stores that had the original layout. Due to these results, the Manufacturer and Retailer came to the conclusion that both the new pack design and the new positioning were successful. The Manufacturer went on to replicate the business case at other Retailers, and the “new look” brand went on to be repositioned within a large part of the market place.

Shelf space – the final frontier?

Getting a brand listed in the key retailers is only part of the challenge facing FMCG manufacturers. Once the product is in-store, there are still a number of pitfalls which could prevent it from maximising its sales and profit potential. Is the product appearing on shelf as agreed with the retailer? Or are out of stocks occurring? And is your product getting the space it deserves?

A leading grocery retailer decided to extend the overall share of space it gave to the moisturisers category on the fixture, at the expense of facial cleansers. A health and beauty manufacturer with brands in both categories was threatened with losing half of its cleanser facings and shelf space.

The issue was discussed in order to plan a defence strategy. It was decided that a combination of named account data and actual shelf space measures should be used to defend the manufacturer’s position and highlight other competing products that had a level of space that was not warranted given their sales performance.

The space-to-sales analysis conducted was wide-ranging but highlighted that the manufacturer had a fair share of space in terms of value share of the sector and share of the number of lines stocked. In terms of linear shelf space, it convinced the retailer of the benefits of increasing its allocated space. A rival manufacturer was highlighted as being over-faced.

New space planning software revolutionises the space planning process

"Merchandising Space Automation" (MSAX by Nexium), generates hundreds of planograms each day and Makes putting the right high revenue, high profit products in each store simple"

Retail Smart Ltd, the leading provider of range and space planning solutions for the FMCG sector, today announced a new member of its space planning product family, Merchandising Space Automation" (MSAX). Intended for use by manufacturers, brokers and retailers, MSAX is critical to achieving the long held goal to optimise the performance of retail shelf space.

Merchandising Space Automation is an easy-to-use desktop and server based software application that leverages rules-based automation to revolutionise the retail space planning process. It combines assortment, capacity and merchandising rules to generate hundreds of unique planograms per planner per day and makes true consumer-centered merchandising possible. In addition to productivity improvements of between 60 and 90 percent, Merchandising Space Automation generates planograms that result in improved inventory turns, more balanced days of supply, assortments that meet local demand, while being easy to shop and aesthetically pleasing.

It is an important ingredient in managing local in-store inventories, ensuring optimal in-stock positions and facilitating precise local execution.

"To achieve category growth and at the same time increase consumer satisfaction makes for a complex formula. Getting the range of products and display right at point of purchase is proven to increase your market share and customer loyalty. For this reason alone more consumer focused planogram need to be implemented in store,” said Jared Joseph, Director of Retail Smart. “Until now, building localised consumer focused planograms has largely been an impossible task, due to the manual process of space management applications.

Merchandising Space Automation forever changes the space planning landscape with an easy-to-install and use desktop and server solution, that will put the right products in the right place on the shelf, with enough inventory to ensure adequate stock between deliveries."

Recognising that critical factors such as income, education and ethnicity drive purchasing habits, and that addressing space planning at the regional level is no longer adequate, it makes cluster- and store-level space planning a reality that was not attainable with manual or one-size-fits-all approaches.

Merchandising Space Automation enables space planners to rapidly model and evaluate merchandising and assortment rules, eliminate unproductive inventory, select optimal planograms and generate higher revenue and profitability. Unlike other space planning offerings, Merchandising Space Automation users report that they can install and begin using the product productively in just a few days.

From Insights In-store to Profits In Your Pocket

Richard Lawrance explores the benefits of store level data & merchandising

The return on investment (ROI) generated by different types of in-store activity is vast. Information Resources (IRI) has found for example that new in-store fixtures or display stands provide an average increase in sales of £1.60 for each £1 spent on the activity. In stark comparison, in-store sampling, and direct marketing on average provide a return of less than 20p of additional sales per pound spent. Other media found to be successful were the use of in-store merchandisers (people who go in-store to check and correct the fixture layout), and in-store posters, delivering £1.36 and £0.95 per £1 spent respectively.

“My theory for the varying ROI from different in-store activity is that the closer an activity is to the point of sale the better the short term uplift – although more “remote” media (eg TV) will have a bigger long term impact”, Richard Lawrance, Senior Consultant, Information Resources speculates.

To reach these insights we compiled a database using information from its recent evaluations of in-store and local marketing media. It highlights the large differences seen in return on investment gained from this type of activity. Activity types analysed included in-store demonstrations, new display stands, frequent re-merchandising activity (changing the shelf layout), in-store posters and direct marketing.

Lawrance explains, “Using this comprehensive and unique database of store-specific sales data, our consultants can group a retailer’s stores into those that have received certain activity and compare this to a group of similar stores with no activity. By factoring out the expected sales trends, we are able to isolate the uplift in sales from the activity in question”.

In addition to this type of evaluation, other store level research has shown that return on investment increases when the activity is targeted to high potential stores or shopper demographic.

Value of the store level

Realising sales opportunities isn’t easy. But by knowing what’s happening in-store – and there are nearly 2,000 across the leading four major supermarkets alone – you can see the differences between them. The opportunity from exploiting these variations is too good to miss. “The variation in brand share across the chains can be astounding. For example, a major drinks brand with a 52% share of their sub-category in Sainsbury’s, has a share ranging from 33% in one store to 93% in another. If this manufacturer had built their marketing plans assuming the average share, they would be missing the mark in most stores” says Lawrance.

Research by IRI and McKinsey in the US suggests that increasing the sales of underperforming stores to the average can generate an overall 15% increase in sales in some categories. Working with many manufacturers and retailers to help them exploit this opportunity in three key areas: •

  • Planning – identifying where the opportunities are and targeting resource
  • Execution – monitoring if plans are being executed so that remedial action can be taken if necessary
  • Evaluation – finding out how well the plans worked

The best laid plans

The key to a successful marketing campaign is careful planning. Store level data allows this planning to be targeted where it will have the most impact. To take the example of a major pet food brand, 25% of sales in one of the major multiples come from only 18 stores and half the sales come from just a quarter of stores. This is powerful information when planning any sort of in-store activity.

  • Promotions or product launches can be targeted on the top performing stores where the impact on overall sales will be greatest
  • Why are the top performing stores doing so well? Is it the demographic profile of their shoppers? Is it the local competition? Is there some in-store best practice that can be rolled out nationally?
  • Action can be targeted on the underperforming stores to bring them up to category average e.g. field marketing, training, localised advertising or planogram revisions Many manufacturers are using this approach to target field sales teams or field marketing agencies to specific stores.

Recent research by IRI in the US involved dividing the field sales teams of a manufacturer into two groups during a product launch. One group was empowered with store level data, while the other group was not. On average, the group with store level data achieved 39% higher distribution levels than the group without.

Closer to home several major FMCG manufacturers in the UK have realised significant benefits by focusing on just the stores that contribute most to the business. For example by targeting their field marketing agency to address stocking issues.

As well as targeting, store level data can be used to plan tactically at a more local level. As many of the major retailers are moving away from national planograms, this gives brand owners the opportunity to exploit local variations in demand. Range, merchandising and other marketing tactics can also be modified according to the different competitive environment found in various store formats. Consider one major food brand with a 40% share in most Sainsbury’s stores, but over 60% share in the smallest stores. How will their tactics be different in the smaller stores where they are the only brand compared to larger stores where the fixture is more competitive?

Look and learn

Given that 85% of new product launches fail, it is critical to monitor sales during the first few weeks of a product’s life so that remedial action can be taken if required. Store level data allows this action to be targeted where it is needed. One launch by a major food manufacturer last year showed a significantly faster distribution build in Asda than in other retailers. The reason for this was their ability to access store level Retail Link data to monitor distribution and take direct action where there were problems.

Even where a launch is successful in terms of attaining distribution targets, there are many opportunities which can be uncovered using store level distribution data. One recent confectionery launch achieved over 80% distribution in Sainsbury’s in the first three weeks, and generated over £125,000 of sales in the first 12 weeks. Yet even in this successful launch, 75 of the 100 largest stores suffered at least one week out of stock, and five of these stores did not stock the product at all. If these issues had been addressed, the product could have realised an additional 10% in sales.

Richard explains, “Store level availability data can be used to identify ‘repeat offender’ stores, target field teams, spot patterns and evaluate lost sales. Sales and price data can be used in a similar way to monitor the execution of pricing and promotional plans”.

Maximising your investment

Of course, overall objective of any marketing campaign is to increase sales. According to Lawrance, “A major food brand recently used one of the leading field marketing agencies to maintain stocking levels and merchandising in store. By comparing sales in the stores on the call file with a control group, the sales impact was worth £3.72 revenue for every £1 spent with the agency. This compares favourably with IRI’s benchmark of a £1.36 RROI [revenue return on investment] for merchandising activity.”

Store level data provides an effective way of demonstrating payback from localised activities by comparing sales in a test panel of stores that received a particular activity with a statistically matched control group of stores that did not. This technique has proved highly effective in evaluating activities as diverse as direct marketing campaigns, field marketing agencies, poster sites, local radio advertising, merchandising, POS and localised promotions.