[Cas réel] Sears / Kmart: engage 100% of in-store mobile customers. Without App. With Artificial Intelligence

by bold-lichterman

In summary

:: The consumer prebiscites the Mobile devices offering them a real advantage (L’Oréal, Target, Macy’s…)
:: A new solution makes it possible to address customers without an app, in the store
:: It improves with each visit by embedding artificial intelligence.

In details

Are consumers angry with retail apps? Yet, when presented with useful services, they nod. Three announcements came to confirm this last week:

L’Oreal: Building on its initial successes, L’Oréal has just acquired MobiFace, its subcontractor for 4 years and the creator of its virtual make-up and skin diagnostic applications. These real technological jewels can be used, as specified in Figaro Lubomira Rock, chief digital officer of l’Oréal “both on the applications of our brands, their websites or in their boutiques and counters in department stores”.

Macy’s: after a successful pilot, Macy’s by the end of the year will offer its store customers the ability to pay for their purchases directly in the app in the middle of the shelves in 450 of its stores.

Target: Drive-up, Target’s in-app service that simplifies in-store click and collect, currently being tested in 50 stores, swill be generalized in 1000 stores by December.

But how can this type of service also be brought to customers who have not downloaded the store’s app? They are apparently ready for it, since in France, the survey the Fevad / Médiamétrie survey tells us that 6 out of 10 Internet users equipped with a mobile phone have already used their mobile in store (Q4 2017)

Engage in store, without an app

How many times do you walk into a store, department store, or big box, and that store has no information about you, when you’re a regular customer? The solution discovered in January in New York at NRF wants to change that.

Goals :

– Provide in-store service that builds loyalty

– Increase in-store engagement and sales

– Increase the average basket.

The solution – Mobile Engage, offered by Retail Next, the global leader in store analytics, based in San José, Calif., delivers an app-like user experience and engages shoppers one-to-one, but without an app.

The scenario –

Step 1 : A customer enters a store and is offered the possibility of registering (by just giving his e-mail address, for example) in order to connect to the brand’s Wi-Fi network and receive specific content (Lookbook , Tutorial video, “Deal of the day”, games, coupons, ect ..). In a store Aldo Shoes, for example, (including the strategy to merge physical and mobile commerce is a proven success) a small sign at the entrance encourages users to use wifi inside the store.

If the store does not have wifi, it can send the customer a link by SMS.

2nd step : Of course, the customer needs a good reason to register. The next time this customer enters the store, they will be invited to connect, and will be redirected not to the brand’s generic site but to a personalized URL pointing to a Landing Page Welcome and a Preferences tab. The person indicates their preferences: what categories of products, content, coupons do they want? What is his project? etc.

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SEARS: Preference tab, to collect purchase intentions

Then over the course of their store visits, the customer will be recognized and will receive personalized recommendations, benefits and content based on their preferences indicated in the Preference Center to which will be added their history and purchasing behavior, but also, and this is the strength of the physical store, real-time contextual data (weather forecast, local events around the store, events currently in progress in the store, etc.). Which customer resists a personal advantage addressed one-to-one?

Step # 3: This is where artificial intelligence comes in. Over time and customer visits, the brand will build up an increasingly precise profile of its customer with their preferences and the context in which they shop. Mobile Engage uses learning algorithms to be smarter every time with every store visit. “We rely on two main types of data” explains Eric Dodd, Product Owner at Retail Next :

Behavior in store (traffic, duration, departments visited, etc.) : ” We include this data in the recommendation system ”.

Real time data : ” Machine learning is always fed is in real time, depending, for example, on the weather. If an item is very popular today in a store, we can suggest it more often in the recommendations of like-minded customers visiting that store today. Perhaps this is due to a local context? (weather forecast, event…). This data is very important for the marketing team, it gives them the possibility to personalize the customer experience. »Says Eric Dodd,

Examples of messages on subsequent visits

Based on preferences collected via the Preferences tab: highlighting only preferred product categories (Ulta); contextualized product recommendations (Dick’s); Personalized coupons (Kmart) and saved in the Wallet (Kohl’s)

Machine Learning that learns from visit to visit and personalizes more finely

Mobile Engage is not a replacement for email marketing, social media, or even an app. It just makes those channels stronger. It works in conjunction with existing campaigns and leverages online and in-store shopping behavior data to optimize a personalized in-store shopping experience.

REAL CASE SEARS / KMART

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The Group: Sears Holdings Corporation (SHLD) is the third largest distribution group in the United States, behind Wal-Mart and Home Depot. In its ongoing digital transition, personalization is key. Shop Your Way® (“At your service 24/7 to help you in the moments that matter”) is a program that offers members advantages for buying not only in the group’s stores, but also from retail partners.

Objective: increase store traffic, increase sales

Device: Sears / Kmart uses Mobile Engage to deliver timely, targeted product offers and recommendations to Shop Your Way customers and members.

Results:

– 1100% increase in the rate of use of mobile offers (vs. static mobile pages, addressed to all customers indifferently)

– 26% increase in the average purchase amount

– Increased knowledge of purchasing behaviors and preferences from known – and unknown customers (not registered at Shop Your Way)

– Speed ​​gained in the implementation of campaigns to test devices using artificial intelligence in stores ((personalized on data and behavior in real time, and sent at the right time thanks to the mobile).

Other Use Case possible

ROI Detect purchase intention – A customer came to the store 6 times to buy shoes. But today this person has come to buy children’s clothes. Whether she made her purchase – or not – this Store data is valuable for the marketing team

ROI Increase the number of downloads of your retail app : On arrival in the store, the URL link sent to the customer can be an invitation to download the brand’s application to benefit from a personal benefit. An immediate way to increase the number of downloaded apps (note: an onboarding program must follow!).

Measure store conversion for Facebook and Display campaigns

ROI In-Store Guest Wi-Fi – Avoid showrooming and reduce the distribution of coupons and indiscriminate discounts, directing the client / propect to the options that correspond to her.

Do customers readily agree to deliver their preferences?

Arun Nair, CTO and co-founder of RetailNext at NRF 2018, that I interviewed in January in New York at NRF, is categorical: ” If customers have a good experience and if the brand continues to deliver relevant and valuable content, customers are generally happy to share personal information. Bonobos, one of our clients, is doing a great job. Every time I come, they recognize me, they know what I like, what I bought in the past, what suits me, they even offer me a glass of champagne showing me products that I will like. I know I’m paying for this service somewhere but I don’t mind. The more I have a good store experience, the more I will come back “.

WHAT MAKES THE SOLUTION UNIQUE

-It relies on the Online AND store journeys to personalize the shopping experience of the customer who enters a store
-It includes a Preference Center: as indicated by the client himself
-It uses machine learning to ensure the relevance and accuracy of personalized messages
-Without app (via wifi)
-Quick implementation – An “Up and Running” in a week or two without calling on IT resources

WHY ARE YOU INTERESTED?

Near’one in two e-commerce purchases (45%) will be made on the mobile in 2021, (tomorrow). US market. Increased competition for the store. Or a chance for those who will recognize and reward the on-site visit with real contextual and real-time personalization. Thanks to AI.

Photo by Xianjuan HU we Unsplash

The correspondant :

All about Visual Research with The Home Depot Best BuyLaurence Faguer is a marketer and entrepreneur “go-between” France and USA, founder of Customer Insight.

At the request of French companies, she identifies in person innovations in Digital, Mobile and Retail in the United States, before they are known in France, then helps them to successfully transpose these successful strategies in the US

Laurence is US expert for FrenchWeb who resumes from time to time the publication of articles on her blog.