How do you inform consumers of the right offers at the right time when they walk in? How can you navigate customers to the right store at the right moment? Startup trakRYT is aiming to provide comprehensive answers to retailers with its real-time analytics solution. The firm provides customers with in-the-moment & aggregated KPIs via real-time analytics, to help better manage non-peak hours. Dataquest spoke to Amit Kinariwala to get a perspective, on how real-time analytics can make a difference.
Some edited excerpts:
What are the gaps in analytics solutions for offline retail, and how does trakRYT aim to address these gaps?
Currently quality analytics possible for offline retail centres largely around operations. The data for this comes from the billing and purchases data. Analytics like sales, sales by SKU, stock in hand, SKU velocity, inventory aging and more can and is being done accurately.
Where offline retail lags behind is in customer side analytics, both pre-buying and post-buying stage — this part is virtually non-existent, even in organizations that run loyalty programs. Questions shared below are not answerable:
· How are customers discovering your store, brands, offers?
– How often do customers walk in and not buy anything?
· How long do customers spend in my stores?
· What sections do they spend more time in? Do I have this information by customer profile like age / gender etc
· Do my customers always provide loyalty number at billing?
· How many of my customers have also visited similar stores in the last few days or months?
· What is the profile of my customers?
· What is the profile of new customers I am attracting?
· How many of my regular customers are not on my loyalty program?
· Do I have a view of customers outside my store? For e.g. does eating out, entertainment habits of a customer lend value to a apparel brand?
· Pushing recommendation to the customer when they are in store and looking to buy rather than later when the customer is at home / office and not really looking to revisit anytime soon.
We are bringing in a view of the customer that offline retail has never had and in real time. This is not just a snap shot, but a longitudinal contextual view of the customer.
What are the key gaps in the current CRM / Loyalty programs?
Currently Loyalty programs and CRM solutions are post event activities i.e. they do not really lend themselves to augmenting customer experience or engagement when it matters most i.e. when the customer is in store. Loyalty programs have become largely points collection and redemption exchanges. As a customer whether I am new to a store or a high spender my experience does not vary brands try and provide a uniform good experience, it is time to move to ‘personalized experience”
Research has shown that what customers most want is a sense of ‘remembrance’, ‘recognition’ and ‘instant gratification’. Most loyalty program are created thinking that giving points leads to loyalty. However many of us own loyalty cards also forget to either use them within the store to redeem them or they expire leading to more frustration with the retailer thus losing an emotional connect with the retailer. This is what RYT brings to the table. We build the connect between the Retailer and consumer when it matters, when the consumer is within store, in the right mood for shopping, and in the right context. We empower retailers to recognize and engage the customer and build a relationship that goes beyond just transactional.
What is the value proposition in creating a real-time analytics platform?
This can be summed up as “contextual relevance”. Most programs tend to segment i.e. put the customer in one silo or the other. Our view is that this is very rigid way and does not lead to value for customer. The customers needs / requirements differ based on the situation / context. For example, I can be experimental on food, but not for clothes. This is like a strategic layer for analytics. Then there is a question of tactical analytics: What is that I am likely to be looking for today / next few days. This is where real or near real time analytics based fulfilment kicks in which the RYT platform brings.
The value we bring for the retailer is in being able to look at a customer as an individual and reach out to them with relevant communication rather than sending out the same message to the mass and hoping for an averages conversions (1-3%).
One of the aspects of this platform we have been obsessed about is in defining ‘relevance’ for customers. It is very easy to flood the customer with messages and let them find ones that is useful for them. Real time analytics helps us provide only relevant message , cut down on irrelevant and non-contextual messages : Right time, Right Place, Right Offer
Can you let us know some use cases where this solution will be extremely useful?
There are many uses cases we are working on, let me give you a brief on some.
Say, you are a regular walking in frequently to your favorite pub every week and being recognised as a regular get excellent service. Now you visit with your friends a different Pub of the same chain but at a different location. You are not recognized as a regular and become totally anonymous to them, the Pub brand has no clue about it being favorite for you. You are not viewed as a premium customer for this brand, and this creates a negative experience of the brand in your mind. We are now able to tell the chain that you are a regular customer in real time and should be treated as such across locations. How cool is that !
Take the case of a bank. Banks spend significantly in creating properties around dining and shopping. This is their moment of truth (spend) where the customer decides which card to use for payment. At present Banks only have access to hard / printed communication in-store (like tent cards / standees ). These communication tools are unreliable, have a short life and are expensive to replace. Banks would love a personal medium that can remind the customer to use XYZ bank card while they are shopping / eating out etc along with a benefit for doing the same (offers). This is their moment of truth !
Then, there are opportunities for cross sell / up sell at apparel stores. The best opportunity for a store to sell more to a customer is while they are in premise. This is what we call ‘Follow the customer messaging’ which works where the customer is and give opportunity for the business to build a persona and be informed about his or her preference or likes and dislikes. This not only elevates the customer experience within the store or business and increases loyalty in the mind of the customer.
And all this much before the consumer has reached the PoS and helped the business think of the relevance of the customers’ needs when they are in store. For example, customer spending time in ethnic formal wear can be made offers on formal footwear, make up etc. Similarly customer spending time in jeans section, can be made offers around casual jackets / whites / shoes that go with jeans. RYT platform allows retail to capitalize on opportunities to provide contextually relevant offers and increasing the visit basket size.
What is the opportunity you have in this space in India?
In the India context this market is huge and virtually untapped. Look at how currently retailer brands, Spa’s or restaurants handle their data. They don’t do much beyond the traditional spray-and-pray sms or email tactics and get a hit rate of around 1-3%. That is a colossal waste of resources and does not bring in the desired effect. By sending an email or sms when I don’t intend to buy, not only irritates me, but also I just delete the message and don’t even remember what was the message when I need it. Which is precisely the pain we felt ourselves and decided to build a platform the retailer can use to understand the consumer behaviour and send messages which are relevant to us as the consumer. The RYT platform works on the basis of understanding the consumers need at the right time, in the right place with the right message.