RETAILERIN

IN-STORE BEHAVIOUR ANALYTICS

In what consists

RetailerIN is an advanced in-store analytics solution, able to measure and analyse in real-time and with high precision how shoppers move and interact with products in a physical store, and to turn such data into actionable KPIs for store and marketing managers to improve processes and optimise store’s profitability.

“You can’t optimize what you can’t measure”. The ability to monitor, analyze, and control healthcare processes and operations, in real-time, leads to better patient experiences, new and improved healthcare services, and safer treatment outcomes.

Solid infrastructure, scalable analysis, interactive web dashboard.

How it Works Grocery Stores

RetailerIN makes use of advanced indoor positioning and sensing technologies to track with high precision (sub-meter accuracy) how customers move inside a grocery store and interact with products.

The information is processed, using cutting-edge big data tools and proprietary methods, to extract relevant indicators and objective metrics on the in- store customers behaviour, including footfall levels, movement patterns and queue analytics.

These indicators and metrics are then used to build visual analytics dashboards for store and marketing managers, helping them to optimize the placement of goods, to measure the effectiveness of store layouts and to improve staff management.

MAIN FEATURES

Interior Analytics

Interior analytics allows retailers to fully understand how shoppers move inside your store, which are the hot areas or departments, as well as the most recurrent shopping journeys. This is the most relevant indicator of shoppers engagement across the store and its departments.

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Foot Traffic Counting & Conversion

RetailerIN advances existing people counting solutions by providing means to understand the foot traffic patterns in your store. This includes not only the number of customers entering your store, but also their loyalty over time and the most recurrent patterns.

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Staffing Optimisation

Through RetailerIN you can adjust staffing levels within the store based on shoppers volume. This can significantly improve the store performance focusing on the right activities at the right time.

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Engagement

One of the key challenges of modern retailers is to find new ways to engage shoppers while in-store, delivering a relevant yet personalised experience to increase conversion and loyalty. This is a fundamental ingredient to increase sales and basket size.

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Sales Associate / Shopper Interactions

Understanding employee paths throughout the store and their interactions with customers is a fundamental ingredient for ensuring the best quality of service. The understanding of where shoppers spend their time in the store, compared to where sales associates do, can provide key insights on how which areas are unserved and on how to optimise store operations.

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Real-Time Alerts and Notifications

Store operations need real-time notifications in order to to maximize effectiveness and enable real-time store management strategies.

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Queue Analytics

Queues, while does not have a direct ROI, certainly impacts the shopping experience of the customer and his/her loyalty over time. Getting details analytics on customers queuing patterns at checkout, wait time at fitting rooms, can give retailer a tremendous opportunity to increase customers conversion and satisfaction. This has an impact on customers throughput and eventually sales.

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Interior Analytics

Heatmap

“ Where do customers spend their time in my store? How long they stay? Which are the most popular departments? Which products they inspect? ”

Interior analytics allows retailers to fully understand how shoppers move inside your store, which are the hot areas or departments, as well as the most recurrent shopping journeys.

This is the most relevant indicator of shoppers engagement across the store and its departments.

RetailerIN provide advanced analytics tools such as the most highly traveled routes within the store and how long shoppers remain in specific areas.

Such knowledge can be extracted from the department level, down to the single product categories. This information can be analysed based on time of day and season.

Once a retailer has identified store high traffic areas, they can implement specific product planning and layout strategies, placing key merchandise in these highly traveled areas to drive conversion, improve sell-through, and promote merchandise. Similarly, this information can be used to ensure the optimal performance of promotional campaigns.

RetailerIN interior analytics toolkit let retailers easily model their store, specifying departments, product categories, aisles, end caps. RetailerIN will then automatically start to compute actionable KPIs to let retailers rapidly identify:

  • Optimise store layout and displays by identifying under-visited areas.
  • Improve customers shopping experience by identifying bottlenecks in shoppers flows and congested areas over time.
  • Increase engagement by creating personalised shopping experiences for specific customers segments.
  • Recurrent shoppers patterns.
  • Engagement with specific brands and promotional campaigns.

Foot Traffic Counting & Conversion

“ How many customers enter my store, with which frequency? Which are the peak hours across the store, as well as the various store departments? ”

RetailerIN advances existing people counting solutions by providing means to understand the foot traffic patterns in your store. This includes not only the number of customers entering your store, but also their loyalty over time and the most recurrent patterns.

Through foot traffic and conversion you can increase sales by identifying best-performing stores and learn best practices that can be rapidly replicated over low-performing stores.

Staffing Optimisation

“ How do you best align staffing to traffic volumes and store operations, while preserving a good store performance? ”

Through RetailerIN you can adjust staffing levels within the store based on shoppers volume. This can significantly improve the store performance focusing on the right activities at the right time.

Based on shoppers presence, it becomes possible to:

  • Reposition sales associates across departments or locations, based on customers presence in the store.
  • Prioritize the activities to perform in the store in order to maximize store operations while preserving an adequate customer support.
  • Re-allocate shifts to align with traffic patterns to improve service levels and maximize conversion, sales, and profit.
  • Receive real-time alerts when a traffic peak is detected.

 

Staffing optimization works both at the store level, but also by department. RetailerIN metrics can determine traffic peaks in specific resource-heavy departments and suggest how to best serve such department during traffic peaks.

Re-allocating shifts to allows to reduce costs, while providing an optimal customer experience drives to improve conversions.

Engagement

Engagement

“ How to implement in-store engagement strategies so to increase customers conversion and loyalty?”

One of the key challenges of modern retailers is to find new ways to engage shoppers while in-store, delivering a relevant yet personalised experience to increase conversion and loyalty. This is a fundamental ingredient to increase sales and basket size.

Sales Associate/Shopper Interactions

“How, where, and for how long your staff interacts with shoppers in-store help your stores achieve their goals?”

Understanding employee paths throughout the store and their interactions with customers is a fundamental ingredient for ensuring the best quality of service. The understanding of where shoppers spend their time in the store, compared to where sales associates do, can provide key insights on how which areas are unserved and on how to optimise store operations.

Real-Time Alerts and Notifications

“How to anticipate needs and manage store operations in real-time?”

Store operations need real-time notifications in order to to maximize effectiveness and enable real-time store management strategies. This includes:

* Opening/closing checkout counters depending on the customers approaching the checkout barrier
* Straightening out fitting rooms after shopper use
* Re-allocating staff to busier departments or store areas

Real-time alerts can also be used to trigger marketing activities such as a proximity marketing campaign to drive foot traffic on slow days, taking advantage of inventory opportunities.

Queue Analytics

“How do queues affect customers experience and store performance?”

Queues, while does not have a direct ROI, certainly impacts the shopping experience of the customer and his/her loyalty over time. Getting details analytics on customers queuing patterns at checkout, wait time at fitting rooms, can give retailer a tremendous opportunity to increase customers conversion and satisfaction. This has an impact on customers throughput and eventually sales. Through queue analytics it is possible to:

  • Prevent in real-time bottlenecks at checkout counters and always deliver the best possible checkout experience
  • Support the dimensioning and scheduling of staffing so to properly handle traffic peaks
  • Obtain measurable feedback on store layout and customer experience