Our highly experienced team of data analysts and business consultants can help you identify business opportunities from transaction and loyalty data. We have experience with more than 300 retailers, including grocery, petrol, convenience, liquor shops, bars, nightclubs, restaurants, hotels, airlines, stadiums, take away food, cinemas, caterers, zoos, theme parks and more.
Utilising our rich industry experience and unique data analytics systems and capability, we identify business opportunities and help structure initiatives with optimal execution through the path to purchase.
Post implementation, we can evaluate trials, measure changes in shopper behaviour, and establish a deep understanding of return on investment. Please contact us to customise a project and team to your requirements.
Test & Control Analysis
We can analyse the effectiveness of store trials by conducting A/B test and control projects. We can assist in the selection of appropriate test and/or control stores, and monitor a range of key performance metrics for a deep understanding of shopper behaviour and sales results.
Measure the effectiveness of in-store displays, ranging, planograms etc.
Store Clustering Analysis
We use data modeling to create optimal clusters of stores. We use static attributes, performance metrics and advanced derived attributes to enhance the modeling inputs. For example: Proximity to competitor stores, Customer Types, Shopper Missions, Buyergraphics, Local Demographics, Daypart reliance, Store Location, Store Size, Features, Qualitative measures, Sales performance metrics etc.
Promotion & Price Optimisation
How successful are my promotions? What are the most effective mechanics and price points. Do they grow number of transactions or increase items per transaction? What was the redemption rate of my Multibuy promotion? What impact does catalogue have one my sales?
We can help with deep analysis to optimise the promotional strategy.
Product Range Efficiency
To optimise range, we first want to understand the role different products play. What type of customer do they attract, on what type of shopper mission, at what time of the day? Overlay sales performance metrics and any unique attributes that enhance performance of the range.
Create different ranging scenarios to optimise category performance.
On Premise Behaviour
Deep analysis to understand purchasing behaviour in pubs, bars & hotels.
How does it change from the 1st drink of a session, to their 2nd, 3rd, 4th and subsequent drinks? How many people stay on the same drink they start with? How does purchasing change by time of day and day of week? Which drinks are popular with food pairing's in meals, versus a drink for one, or part of a shout? What are the promotional opportunities?
Access competitor intensity, and use regression analysis to understand which geographic factors are affecting your performance. How does store proximity interact with other store attributes and performance metrics.