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At the end of the 2018 Retail Big Show in New York, attended by SQLI Lab teams, the question arises: what are the main trends that will impact the retail industry this year? If technologies have a big role to play in the future stores, the human aspect, reflected by the customer experience, will also have a very important place to hold. The SQLI New York Lab explain these trends for you.

 

Customizing your products:

Nike Make it Your is an example of customize your products Even if the concept of customization is not recent, we can see that retailers are increasingly innovating in order to offer customised experiences to their customers, Whether you want to buy sneakers, glasses or enjoy a unique experience, brands are working hard to offer products that are unlike any others. Not only are customers attracted to brands but they also want a product or a personalized experience. At Nike or Converse in Manhattan, a full floor of the store is dedicated to personalizing your shoes: from the color of the laces to the printing of specific words, anything is possible. What matters is that the customer is the actor of this customization. Previously, he/she was offered different models from which to pick. Now, the customer is the one in charge of the design: at Nike, one designates the color of the logo, the inscriptions on the sneakers or the color of the laces.


The Battle of the platforms:

The Amazon vs. WalMart war will continue in 2018 and will above all show the need for brands and stores to become global platforms. WalMart is increasing its online presence through numerous acquisitions to counter Amazon, which is trying to reinforce its proximity with customers by opening its own bookstores or buying existing store chains such as Whole Foods. People do not go to stores (offline or online) to buy a product, but to benefit from the services coming around this purchase. This platform translates into in-store service offerings, which come before or after the purchase. We can see online that the big players all want to become global platforms: Uber recently launched a credit card, Airbnb is involved in the booking of airline tickets or restaurants. This kind of platform requires a very powerful IT infrastructure. In the physical world, we can see that coworking space leader  WeWork recently acquired Meetup to develop its platform dimension.

Regarding stores, the latter will have to insist on their ability to deliver service as quickly as possible and facilitate the act of purchase, which brings us to the next trend.


Cashless stores:

Stores have been becoming more and more cashless. In the United States and around the world, fewer and fewer in-store transactions are made by cash. In 2016 a Gallup study () showed that only 24% of Americans were shopping only using cash and American point-of-sales have been adapting themselves to this trend. Amazon has been opening cashless stores, Nike has also been experimenting in this area, and Starbucks is currently pushing the use of in-store mobile payment to limit the use of currency/ after they announced that 11% of their orders are now made through a mobile phone. Numerous technologies allow these payments: the main tool being the classic banking card, NFC, mobile apps and bitcoin are starting to take an increasing place. If you are expecting a frictionless experience in store, making payment easier is a crucial point. Cashless stores are therefore necessary. The risk of burglary is lower, and this model especially brings the experience of spending less time buying. But above all, a cashless store can be designed differently as fixed cashiers are not need anymore. Instead, the salesperson can be equipped with a mobile payment terminal and stand by the customer to assist in his/her purchase process.


Data, data, data:

whether in data security or in their use, data will be once again the buzzword of 2018. Physical stores have increasingly been leveraging Big Data, an essential strategy for Amazon's success, and applying it to optimize buying experiences and business management.

 

Hence physical stores players are more and more using data collection and analysis tools to evaluate shoppers’ behavior. These tools are required in order to optimize stores products’ prices, to provide more personalized marketing and to better predict store demand variations. In 2016, the brand True Religion () tested on Apple Watch app that warns the in-store employees of the arrival of customers; those customers already having installed the brand’s app and having made at least one purchase before. The salesperson, therefore, has a global view of the customer on his watch, with his/her tastes and frequency of purchase. These data enable the salesperson to guide the customer along the lanes. This type of initiative should be more and more prominent in points-of-purchase.

Unfortunately, we realize that this is not often the case. According to this Alteryx study, if many retailers do collect data, most of them do not use them effectively. Still, according to this study, only 16% consider themselves as data collection experts, while 24% and 60%, respectively, describe themselves as "novices" and "in the process of getting there".


scaled agile framework

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On the 30th November last year, SQLI presented feedback on the operating experiences of SAFe (Scaled Agile Framework) and DEVOPS before a crowd of a hundred or so people, who had attended expressly to hear the account of Eric Chambefort, Head of the Digital IS Department of EDF Commerce for Enterprises and local authorities.


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A recent requirement from a customer was to be able to target new customers and present them with specific content. The first question is what exactly is a new customer? Is it a first time visitor to the site? An anonymous visitor who has yet to register? A registered customer but someone who yet to make a purchase? A customer whose last purchase was a long time ago, for instance 2 years? To target "new customers" can be a bit troublesome. A clever solution to the problem is to turn it on its head; assume all visitors to the site were new customers and then to segment customers into various groups.

Advanced personalization is achieved in hybris through the BTG (behavioural targeting groups). hybris provides a number of out the box rules (operands) to classify customers into segments. There are many ways to present targeted content to customers in hybris but the basic process involves the following steps:

  1. Set up the content components for each customer segment you wish to target. 
  2. Create customer segment based on the rules available. This can be done in 1 of 2 ways via the CMS cockpit:
    • In the Customer Segments perspective 
    • Create segmentation rules from Customer Segmentation Perspective
    • or can be created via the content component the Context Visibility section:
    •  Customer segmentation from the content component
  3. Assign the customer segmentation restriction to the content component. 

Both positive and negative segmentation rules can be applied; show content based on meeting rule or hide content based on meeting rule. Highlighted below are 2 scenarios for targeting different customer types:

  1. Target new customers:

As mentioned above there are are a number of possible scenarios how to define a new customer. Bespoke operands can be created for such purposes but as this requires development, an out-the-box approach was sort to meet the targeting requirements. Therefore inverting the targeting rules assumes that all customers are new customers and group existing customers in targeted groups. As such, all customers who visit the site are assumed to be new. The default content for the site is targeted to new customers. Targeted content for existing customers will replace the new customer targeted content when a customer falls into an “existing customer” group.

Existing customers can be targeted through various out the box rules including:

  • Last order date :  example - last order placed before 1 year ago
  • Total amount of orders to date: example – the last order was greater than 1 GBP
  • An alternative approach is on registration the user is assigned to a particular security group (for example RegisteredUser) and targeting is then based on the user group (note this will require some customization to ensure registered users are assigned to this user group):
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  1. Target customers based on their browsing behaviour

There are a number of out the box operands to target customers based on their browsing behavior. These fall under the Website Rule set. Two examples are:

  • Has viewed  products: example – a user who has viewed a particular product:
  • Has viewed  categories: example – customer has viewed the cameras category page:
  • Has viewed content pages: example – a user who has viewed the homepage:

 

Target customers based on their affiliate shopping behaviour

There are two out the box Website Rules that can be utilized to target customers based on their affiliate shopping behaviour:

 

 Conclusion

Illustrated herein are a number of options for classifying and targeting customers based on a number of criteria and scenarios. hybris BTG functionality provides a rich selection of rules from which to start segmenting customers. Should you require more complex rules, bespoke operands can be developed to meet your specific requirements.

 

 

 

 

 


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