Business Analytics in retail

Setting trends and reducing exchange rates

Challenge: 
Buying shoes can sometimes be complicated, especially online. A shoe retail chain with an online shop was looking for a solution to reduce returns and identify trends early on.

The solution:
Business Analytics utilises data from online shops, local retailers and social media. This allows fashion trends to be identified extremely quickly. The return kings were also identified and a new routing between online and brick-and-mortar retailers was established.

Benefits:
The return rate fell by 40%. At the same time, customer satisfaction increased. Depending on the product, customers are directed straight to the online shop or to the shops. This means that even "difficult products" sell without being exchanged.

Enhance fan experience and team performance

Challenge:
In professional sports, revenue and efficient training ensure top teams. A basketball club is using new ways to make stadium visits more attractive and improve the team's performance.

The solution:
Business Analytics processes data from ticketing, geodata from mobile phones and camera data to improve the fan experience. Matches, training sessions and player health data are also analysed to help prepare for matches.

Benefits:
Shorter waiting times at the stadium and attractive merchandise offers increase sales. New training methods and improved playing tactics have resulted in a significantly improved league position – and even more fans.

Optimise sales, pricing and inventory

Challenge:
A supermarket chain has high write-offs due to food items with expiring use-by dates. Unsold goods are written off manually, which often leads to inaccuracies in inventory management.

The solution:
Business Analytics links product inventory, expiry dates and sales prices, and incorporates external data such as competitors' prices. Food items are offered at promotional prices shortly before their expiry date and optimally placed in the market. AI ensures more accurate forecasts for reordering.

Benefits:
Increased sales, fewer write-offs and optimised reorder quantities reduce costs. Automatic data transfer to the merchandise management system reduces the workload for all staff.

Reduce transport times, reduce complexity

Challenge:
A logistics company with an estimated 8,000 vehicles delivers over 500,000 parcels every day. Tight delivery deadlines must be met without fail.

The solution:
Business Analytics optimises the planning of thousands of different routes every day. Factors such as weather, current traffic conditions, parcel and customer data are taken into account. Business Analytics ensures faster tracking of shipments.

Benefits:
Increased adherence to delivery schedules within specified time windows, reduced transport times and faster parcel tracking. It also reduces the workload for staff, as data consolidation reduces the number of programmes used in parallel.

Greater transparency for greater efficiency and turnover

Challenge: 
The goal is to provide excellent services and an attractive shopping experience by linking the local point of sale with the digital world. Intelligent sensor technology at the PoS is the next logical step on the way to achieving this.

The solution: knowing
the number, age, gender and length of stay of your customers at each location allows you to optimise staffing and marketing efforts. Video analytics provides an overview, while AI analyses of shelf levels and product interaction add further value.

Benefits: Product
range optimisation and targeted customer engagement with in-store analytics ensure greater efficiency, higher sales and the merging of offline and online customer experiences – as well as a real competitive advantage.