Revolutionizing retail planning with Motion Data analytics

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With the rise of digital technologies and businesses, there has been a noticeable shift towards online channels as a means to boost sales for retail companies. However, it is undeniable that the impact and experiential aspect continue to play a crucial role in attracting customers to physical stores. Whether it's high-end clothing brands like Zara or H&M, offering a wide range of options in their premium stores where customers can try on different clothing and make well-informed decisions, or fast-food chains like McDonald's and KFC, providing seamless drive-through services, having a physical presence is still highly desirable and, now more so since the pandemic effects are gradually going down.


However, how do businesses in this situation determine the specific areas to concentrate on for expanding their operations and which locations would yield the most positive results in terms of increasing sales amidst intense competition? Additionally, what are the appropriate metrics and key performance indicators (KPIs) to consider in order to make the final decision? It is widely recognized that employing conventional methods such as conducting area surveys or analyzing location demographics would require significant amounts of time and resources, while offering limited metrics to base subsequent decisions on, whether it involves proceeding with the current location or exploring alternative options. Therefore, it is crucial to have access to tools and expertise that enable a deep understanding of customer needs and provide a comprehensive collection of established KPIs derived from an extensive time period, facilitating better strategic decision-making. This is where Motion Data emerges as a groundbreaking technology capable of delivering numerous customer analytics and geographical insights by utilizing anonymized mobile signal information from Deutsche Telekom, Germany's largest network.

As mentioned in our previous article, Motion Data utilizes mobile signal information from Deutsche Telekom's network and combines it with user demographic data to offer compelling use cases and insights based on customer behaviors. User information is anonymized, ensuring compliance with GDPR regulations and safeguarding customer privacy. One notable area where Motion Data excels is retail analytics, which provides a range of KPIs and metrics for retail planning. These KPIs can be evaluated and translated into tangible action items. The significant advantage of employing Motion Data's retail analytics is the speed at which it generates visibility and transparency, enabling swift decision-making and facilitating rapid expansion efforts.

Lets’ say you are a supermarket chain seeking to identify the ideal location of your next store in response to increasing customer demand in the state of Hesse. Currently, you have multiple stores operating in places like Wiesbaden and Hochheim am Main, and you are considering entering the city of Frankfurt as the next potential market. However, Frankfurt presents various challenges, including intense competition, significant disparities in purchasing power, expensive rental options, and diverse customer preferences. In such a scenario, you can leverage Motion Data to perform analytics on several key areas to determine the most suitable location for your next store. Additionally, Motion Data will assist you in identifying areas that you should avoid due to the aforementioned factors, which are unfavorable for your products and business offerings.

Visitor density information

Figure 1: Catchment area – Visitors per km2, Visitors per inhabitant

 

To effectively understand customer movement in key focus areas, there are several metrics that we can explore:

  • Visitor count: This metric involves tracking the number of visitors in a specific area over a designated time period, whether it be on an hourly, daily, weekly, or more granular basis. By analyzing visitor counts, we can identify areas that experience frequent customer visits, providing an opportunity to attract visitors to our stores. Refer figure 1

 

  • Competitor analytics: By examining visitor counts and other relevant KPIs, we can gain insights into how competitors are performing in those areas. This information can be valuable in shaping our decisions and strategies.

 

  • Demographics: Motion Data also offers detailed demographic information, such as age, gender, zip codes, and potential spending power. This data allows for a better understanding of the customer base in specific areas and helps tailor marketing efforts accordingly.

 

  • Drive time across zones: This metric is crucial as it indicates the time customers spend commuting across different zones, categorized by various drive time buckets (e.g., less than 10 minutes, less than 20 minutes, etc.). It highlights opportunities to target zones where we can reduce drive times and serve potential customers more effectively than the competition.

 

These examples illustrate just a fraction of the valuable insights that can be obtained from metrics, and Motion Data goes even further by offering comprehensive analytics for precise decision-making. Let’s go over some key benefits that Motion Data provides in comparison to usual retail planning methods:

  • The speed at which reports are generated and interpreted, along with the ability to make key decisions based on them, is significantly faster compared to traditional expansion methods.
  • Additionally, Motion Data provides greater accuracy and a larger sample size for analysis, enhancing its effectiveness.
  • The availability of historical reports adds credibility and enables trend comparison, which is invaluable for store planning.
  • Importantly, all of these advantages come at a lower cost compared to legacy methods, highlighting the cost-effectiveness of Motion Data.

These capabilities serve as a significant differentiator and a core asset that can be seamlessly integrated into any organization, driving substantial business growth, and improving competitive positioning.

Robin Reji Philip
Robin Reji Philip

Product Manager - Data Products

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