Our commercial intelligence informs many important and strategic business decisions, including the situations below, for which we have the following case study examples.
A well-known home furnishings retailer wanted to identify the actions to undertake in order to sell more fitted kitchens to their shoppers.
We Surveyed their existing shoppers, both qualitatively and quantitatively, to understand kitchen purchasing dynamics. Then we undertook accompanied shops with kitchen buyers to understand the purchase journey and identify problems and issues encountered. We also spoke to a representative sample of recent kitchen purchasers to understand which retailers they considered, bought from, and why.
This allowed us to create a segmentation of propensity to purchase with our client, potential spend value, and motivations for purchasing. We provided recommendations on which customers should be targeted and how to target them via advertising, social media and in-store services.
We helped redesign the in-store experience for our client and worked with their media agency on a marketing campaign. Our client increased market share by 3.8 percentage points in the two years after the project.
One of the leading beauty retailers in the US wanted to benchmark their own growth against public and private retail competitors.
We used a combination of research methodologies to estimate the sales performance of private retailers, including:
- Consumer research to understand penetration rates and transaction values of customers exiting store.
- Analysis of price points and average basket values.
- Sales density cross-check analysis
Data from the metrics was then put into a model to ensure that they made sense in terms of the wider financials of the company. The data was finally cross-checked against our wider market model and against total retail performance over the period being examined. Finalized data was presented to the client with analysis to explain the trends.
Our client used the data to determine the effectiveness of their marketing, allowing them to streamline spend.
A mass merchant wanted to understand the likely pattern of store development by rival players and the impact on their business.
We gathered existing data on store development plans, which stretched only to the next couple of quarters. This data was supplemented with forecasts as to where future stores could be opened; we did this by assessing the types of locations rivals had traditionally picked and looking for similar locations in terms of demographics, catchment size, and market potential.
Our team mapped this store development potential over a number of years to show what store distribution might look like in the future.
The overlap with our client’s stores was assessed and using data from locations where stores already overlapped, we calculated the potential rate of sales attrition.
We then developed a number of scenarios to provide an understanding of different rates of attrition.
Our client used the data to identify where future store investment could be most effectively directed.
A major apparel retailer wanted to understand how their prices across a range of products compared to those of its rivals.
We helped our client define the competitor set relevant for the exercise using internal consumer research data, then used shopper insight to create a basket of the most regularly purchased apparel products.
Our team of auditors visited a representative sample of stores for both our client and its competitors, and in each retailer the lowest price for each of the items in the basket was recorded.
Other details, such as discounting and style and quality information was also recorded for reference.
Once the audit was complete, we analyzed the spread of prices and created indices to compare the competitor set, both for the overall basket and for individual products, we then provided recommendations on which prices could be adjusted.
Our client increased prices on a majority of products, allowing them to increase profit while remaining competitive.
A department store wanted to explore the commercial feasibility of expanding into new countries, and understand the likely returns.
Our team mapped out the size and scale of each country in terms of consumer expenditure across categories relevant to our client. We then undertook an extensive program of research to understand the shopping dynamics and habits of consumers, looking at things like brand and retailer preference.
This research was used to create a ‘relevant’ overall market size.
We created an ‘addressable’ market size by removing consumers who were not receptive to our client’s range, offer and price levels.
This market size was further refined to a ‘serviceable’ level by removing consumers whom our client could not serve with their proposition.
An ‘attainable’ level was calculated by removing consumers who were unlikely to switch to a new retailer as they were satisfied with the ones they were using at present.
Finally, the attainable market was used to calculate potential sales and shares over a number of years and under a number of scenarios.
Our client decided that the opportunity was not sufficient to justify the costs of expansion – saving them millions.
A US property firm wanted to understand how the retail landscape would change over the next five years, and what it meant for their business.
We mapped out the key trends that were set to change retail over the next ten years using a combination of executive interviews, internal brainstorming, and analysis of proprietary data and insight.Each trend was then scored in terms of the strength of its impact and its likelihood; this created a trend and impact matrix.
A subsequent meeting with the client’s executive team allowed u to understand their business plans and challenges over the next ten years. Our team used this understanding to explore and identify the trends that would be most likely to affect our client.
For each relevant trend, we analyzed the potential impact on the business and also mapped out the opportunities and challenges it presented.
The results were delivered through a workshop session with the client’s executive management.
Our client used our insight and the outputs from the workshop to develop a ten year plan.
A grocery retailer wanted to understand how online shopping was changing the way in which consumers used their physical stores.
From the retailer’s customers, we created three segments:
- Those who shopped online for grocery regularly.
- Those who shopped online occasionally.
- Those who did not shop online at all
We employed a diary-keeping exercise to understand how and when these different groups shopped for groceries, what they spent and where they visited. Accompanied shops were also undertaken with a sample of consumers from each group to understand their in-store behaviors.
Our team analyzed and compared the data from the different groups to detect and identify differences in store behavior across factors like spend, categories visited, categories bought, routes taken around the store etc. Based on this insight we recommended how store layout should be changed to maximize sales to all groups, but with a particular focus on online shoppers who were less inclined to visit all parts of the store.
Our client used the research to optimize store layout and saw sales and basket size increase as a result.