Although the customer leaves an invisible data trail in the store, brick-and-mortar retailers barely use them to improve customer service – its time to think again.
Redefining Analytics for Retail Stores: A Lesson from eCommerce
Data by nature: Why eCommerce analytics are steps ahead
Online retailing not only created a new way of shopping, but it also changed the game when it comes to tracking and analysing the shopping journey. There is almost nothing that is not being evaluated while surfing the webshop. Digital-heat-maps of individual online sessions are analysed, showing every click and scroll through the online store. Every possible KPI is monitored: Conversion rate, click-through rate, average order value, the relation between new and returning visitors, bounce rate and retention to name a few. The really powerful thing about this is that analysis is always followed by action, to improve both the effectiveness of the webshop and the experience of its customers.
Data by design? Time for brick and mortar to take some lessons
Naturally, eCommerce has a significant advantage when it comes to analytics, a digital channel is always going to produce more data. Brick-and-mortar stores need to adapt to compete however, and technology is trying to bridge this gap between the physical and digital. Some of the more hardware-heavy options include AI-powered cameras, smart shelves or even aisle-roaming robots.
While hardware-intensive solutions like customer-tracking smart cameras are available, with the right software supporting it, a technology that simply tracks products (such as RFID) and leverages the IoT (Internet of Things) can revolutionise analytics for stores. These technologies and their supporting platforms are a big driver of ‘Digital transformation’ which delivers the analytics and data that brick-and-mortar stores are desperate for.
Here are 3 lessons from eCommerce for improving analytics in retail stores….
The need for real-time data
For years, brick-and-mortar retailers have been complaining about imprecise stock-figures and unreliable historical data. Unhappy with its purchasing decisions based on last year’s sales figures, retailers would prefer to have real-time data and inventories that allow for reliable and economically viable decisions. After all, it is important to avoid high-security stocks in order to reduce capital tie-up.
But why do we actually have this problem? Are the data points offered by the ERP systems not enough? Unfortunately not – it is not unusual that the ERP system shows higher stock than actually available on the sales floor. This so-called “ghost stock” is the cause for various problems in sales, e.g. the ERP system says a certain article, for example, a red skirt in size S, is in stock, but in reality, it is not. It can neither be sold nor refilled from the central warehouse – a classical out-of-stock situation. Or vice-versa, the ERP displays a lower inventory level than is actually available. The reason for these deviations is insufficient accuracy in individual processes that dangerously sum up over time.
Today’s intelligent article management is based on three pillars: fast, RFID-based article identification on item-level, tracking of every movement in real-time and proactive analysis with concrete recommendations for actions to take for the sales personnel. This is the foundation for optimum customer service and efficient processes.
What does real-time data mean for Brick and Mortar Stores?
- High Stock accuracy
- Increases product availability of the shop floor from accurate replenishment
- Allows for convenient omnichannel services like click-and-collect
- Equips store staff with up-to-the-minute stock information – allowing them to assist customers better
Meaningful KPIs in the store
When measuring KPIs, the practical benefits for retailers are paramount. Three areas of data in the store can be distinguished:
KPIs for Store performance
Whether five or 800 stores, KPIs for measuring inventory accuracy are significant for every retailer and still represent one of the main challenges in today’s business. Retailers, on average, can actually make accurate statements on just about 75% of their inventory (based on SKU level). However, this is not enough to meet customers’ expectations for omnichannel services. Therefore, inventory transparency and corresponding KPIs are essential for retailers´ success.
Product availability on the sales floor, also known as on-floor availability, is the second central parameter. Initially, it is less about the exact position and more about the fact that the articles are on the sales floor – after all, only items that are actually available can be sold. This key figure can be combined with an alert system that makes sure not to fall short of the defined minimum availability. Complementary to classical ERP-systems, RFID-based merchandise management takes the data granularity to the next level, by knowing exactly at each moment in time if products are really on the salesfloor or still lingering in the backroom of a store.
KPIs for individual product & campaign performance
Product dwell-time on salesfloor
Having data on item level, store managers are also given important information on the dwell times of articles on the sales floor. This information is more valuable than simple sales data, as it tells us the average time individual products spend on the sales floor before being sold. This can be used to gauge whether products are performing & corresponding with the sales plan. Common recommendations made from this data include moving items do a different location on the salesfloor (i.e. adjusting the planogram) or relocating excess inventory to another store – both of these measures reduce profit-sapping inventory bloat and end-of-season markdowns.
Fitting room conversion rate
One of the most famous KPIs in e-commerce is the conversion rate that describes the ratio between purchases and website visitors and also provides information on certain items that were already in the shopping cart, but for some reason have not been purchased in the end. Specifically, this aspect was incredibly difficult to measure in the store for a long time but can now be measured in fitting rooms using IoT and RFID technologies. This provides meaningful insights into how many, and above all, which articles does a customer take into the fitting room and which one does she/he actually buy?
KPIs on customer engagement and service quality
On an operational side, KPIs can also be used to manage service quality. We’ve already covered product-availability and stock accuracy, which affect the customer just as much as the store with out-of-stocks or unavailable sizes being all-too-common pain points. The replenishment rate provides another angle to combat this, as it shows how quickly articles are replenished on the sales floor. On the other hand, the fitting room response time describes how quickly sales personnel handle customer requests coming from the fitting room. The KPI “Conversion rate per campaign” shows the success of a campaign and if campaign-specific countermeasures are necessary.
Turning data into actions
The final lesson brick-and-mortar retail should learn from the webshop? Turning data into actions. Since nobody needs a data graveyard, any analysis needs the goal of creating immediate actions to improve. Today’s systems help the management team as well as the store personnel with concrete and automated recommendations for actions to take. This saves time in the decision-making process, unburdens the sales personnel, and enables them to do the right things at the right time.
KPIs should be suitable for everyday business use. Presented visually and self-explanatory, they need to be linked to clear recommendations for actions to take. This frees up store personnel time and provides a data-driven way of optimization. Examples range from simple in-store replenishment advice, i.e. “The minimum stock for article #47699-0010 has been reached – please refill three pieces” to more advanced topics, e.g. to choose a different placement in the store for a specific article when the dwell time on the sales floor is too high compared to other stores. Advanced systems can even utilise AI and Machine learning to automate and refine certain processes, like adjusting store planograms and creating optimal pick paths when replenishing stock.
Brick-and-mortar retail needs support and an update to the toolbox when it comes to analysis and measures. Not only does the sales personnel benefit from intelligent recommendations for action, but the management team also gains efficient control mechanisms across the entire store network. Decisions are made based on real-time data and therefore allow timely action. Ultimately, the end customer is pleased about a first-class service, which – thanks to the individual and informed advice through the sales personnel – even exceeds the standards of the online retail.
Item-level Reporting from
Register for this webinar where we outline the impact of digitisation on supply chain analytics and operational efficiency. Covering the wealth of item-level data unlocked by RFID, the presentation will explain the new KPI’s available for modern supply chains and their impact on retail operations.