Customer Analytics

OST Customer Behavioural Analysis for Retailers

Would you like to know?

  • How many shoppers are interested in, but don’t purchase a certain product?
  • How many people walk in to your store, take a look around and then walk out?
  • How many look at your window display, but do not enter your store?
  • What you could change to increase your stores profitability?

OST can provide the answers and highly actionable insights for your brick and mortar locations. Now you can convert visitor activity data into business intelligence, which translates into increased revenue and profitability. By understanding your customer by gaining full visibility into customer behaviour, in and around your stores, you can improve shoppers’ attraction, retention, build customer loyalty and increase sales.

Micro-Location Technologies

With today’s micro-location technologies, retailers can find out the demographics of their customers, what attracts them into the store and when they make a purchase. The data retailers can now acquire includes:

  • Foot traffic passing in front of store
  • Dwell time in front of store
  • Dwell time in front of store followed by store entry
  • Store entry without dwell time in front of store
  • Dwell time in different areas of store
  • Walk in and walk out with time frames
  • Sales conversions

What this reveals

This technology delivers invaluable insights. You can now find out how many people walk past your store, i.e., the foot traffic around your store location. How many of these potential shoppers pause in front of your store and how many of these actually enter your store can reflect on the effectiveness of your window display. The number of people that walk straight into your store, without pausing at your external window display, can indicate success of your current marketing campaigns and social media activity, as well as brand loyalty. The time an individual spends in the store (timeframe between walk in and walk out) can show the appropriateness of your merchandising strategy. Most importantly, real time sales conversions are instant proof of the state of your entire retail business approach.

Importantly, this data can shed light on why different stores, which appear to be similar, have different success rates (e.g., an observation may reveal different foot traffic passing in front of the stores).

Types of micro-location technology

Vendors can gather information, from a variety of sources, which are capable of capturing visitor trend data such as traffic numbers, shopper direction, average time of stay and even demographics such as age, gender and emotion. These include:

  • Wi-Fi and Beacon technology recognising customer cell phone signals
  • Customer apps to see exactly where shoppers are in the store
  • Heatmaps that show where customers walk in the store
  • Video
  • Monitoring what websites customers visit to identify competitors, whilst they are in your store
  • Recognition technology to track age, gender and emotion

Retailers now having the ability to identify hot and cold spots on the shopfloor, these advanced tools have the ability to identify which specific products attract customers and how many of these customers then make a purchase.

Improved in-store marketing is another benefit, as retailers can use the data generated to better structure messages, and place product and promotional items in prime areas receptive to their target market, as well as measure the effectiveness of point-of-sale displays and marketing.

These technologically advanced solutions can help retailers recognise trends, patterns and abnormalities in customer behaviour, even enabling them to identify security issues and allocate resources accordingly.

Complete visibility empowers retailers

By capturing all interactions between shoppers and products, displays, and behaviour in aisles, you can:

  • Gauge effectiveness of promotions, displays and advertising
  • Provide customers, via their mobiles, with notifications and offers when they are near or inside a store
  • Optimise store layouts
  • Identify the areas of the store that customers visit the most and the least (high and low traffic)
  • Track customer dwell-time data to analyze popularity of store products
  • Make cross-store data performance comparisons
  • Improve staff management by -
    • Optimising staffing levels according to traffic and dwell time to enhance customer service and reduce costs
    • Scheduling support services, such as cleaning and maintenance, for low traffic times
    • Monitoring wait times at checkouts
    • Observing individual staff performance in real-time
      • how long an employee is spending with a customer
      • their sales conversion rates
      • identify training gaps
    • Store employees retrieving data on individual customer profiles such as the purchase history, number of store visits and opportunities for upselling

OST Customer Behavioural Analysis

OST understands that different retail models require different customer data. Heat maps, aisle activity and dwell times in front of store demos and displays, can be important for larger sized stores. Smaller stores are more likely to be interested in foot traffic outside store and number of entries into store. Top end retailers have a need to present a 1:1 relationship with their clients and this clienteling approach requires a dense assimilation of each of their customers’ information.

OST provides consultancy services to help you better understand what your customers want and which micro-location technologies will best meet your needs. By integrating with point-of-sale systems our analytical tools help retailers make smarter, data-driven decisions that attract, engage and retain customers.

Working with our experienced partners, our customer behavioural tools combine traffic information with sales and transactional data to reveal: distribution of traffic by hour, day of the week, store location, seasonal periods, promotion periods, total chain, etc.