From Big Data to Smart Data

data analytics

customer journey

POS/Retail

If you want to understand your end customer, you need time to gather data, analyse it and put it in the right context. Yet without viewing it appropriately, characteristics and deviations cannot be determined. But it's worth taking a closer look in order to understand the motivation of the customers.

Initial situation

Who are my customers? Are we addressing the right target group? Does a busier area also mean higher footfall in-store? Market research 24/7: Is that possible? Our customer STIHL was asking these same questions when setting up their pop-up store in Munich. To answer the questions, we firstly recorded customer behaviour in the store using sensor technology at the point of sale. This enables us to structure the data collected and process it to make it usable.

"It is exciting to see how we were able to help our customer STIHL to derive marketing-relevant decisions from data."

Erim Kansoy, netzwerk P GmbH

Solution

Our use case "Measuring customer behavior at physical touchpoints" describes the structure of the project and the use of our [nP]connect solution. The data collected during the project is aggregated, verified, checked, analyzed and connected by our experts. The combination of different data sources results in a completely new overall picture. Shown in the core element, the interactive dashboard, the customer has access to all important information at all times. Advantage: The effects of measures taken can be followed almost live and adjusted accordingly.

Dashboard

Data sources

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Key figures and KPIs

Result

Based on the evaluation of the generated information, the following insights about the customers and their behaviour could be gained: demographic data (age, gender), time axis (day-by-day to year comparison), frequency/activity in front of the store, time of entries and exits, conversion rate, correlation between number of visitors and turnover, popular times of day, top sales categories, including the most sold products, and much more. Due to the history and the constant data flow, questions such as How do increasing turnover and decreasing visitor numbers behave? What effect does the time of day have on visitor numbers and turnover? How does the average receipt value change? Furthermore, an independently conducted market research of our client reflected the results of the data collection.