Lessons from eCommerce. How brick-and-mortar retail adapts to online standards
Although the customer leaves an invisible data trail in the store, brick-and-mortar retailers barely use them to improve customer service. Dr. Michael Goller, CTO at Detego, explains why things need to change in the future.
Online retailing has not only created a new way of shopping, but also has a powerful toolbox to measure its results – with the overall objective to meet the customer’s expectations at all times. For that reason, online retailing has become the highest standard when it comes to measurement and evaluation in fashion retail. There is almost nothing that is not being evaluated while surfing the web shop. Conversion rate, click through rate, average order value, relation between new and returning visitors, bounce rate and retention time are just some of the KPIs that measure the success of online shopping activities. The really powerful thing about this is that analysis is always followed by action – usually fully automated.
And what about brick-and-mortar retail? It is about time to take some lessons…
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 datapoints 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.
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 inventory accuracy and product availability
- KPIs for campaign performance measurements
- KPIs on customer engagement and service quality
How KPIs are defined depends on the size and number of stores, the assortment depth and the flow of goods. Predefined objectives also play an important role: 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’ 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, an 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. Having data on item level, store managers are also given important information on the dwell times of articles on the sales floor to gauge whether they are corresponding with the sales plan. 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?
On an operational side, KPIs can also be used to manage the service quality. The replenishment rate, for example, states 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 / ©Detego
Turning data into actions
What else can brick-and-mortar retail learn from the web shop? Turning data into actions. Since nobody needs a data graveyard, any analysis of data has the goal to take 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 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 advices, 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.
Brick-and-mortar retail definitely 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 on the basis of 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.