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From Analog to Algorithms – The Evolution Marketing in Retail

February 24, 2018 7:15 am No Comments February 24, 2018

As someone who loves retail and the technology behind it, looking back at how things were done in the past, really lets me appreciate how far we have come. Consumers no longer see a distinction between online and offline shopping. Whether it’s searching on a laptop, browsing main street shops or hanging out at the mall — it’s all shopping. This evolution of shopping behavior has brought some drastic changes in the way sales and marketing operations in a retail set up. The one on one relationship that a corner store thrived on has translated into a different kind of conversation, a conversation with machines. I am not talking about some sci-fi, ‘Ex-Machina’ kind of stuff, but how machines, more specifically the algorithms within those machines are enabling marketers have 1 to 1 conversations: at scale. Imagine you walk into a party and have the ability say a hi, ask a how are you, and have an individual conversation with a hundred, different people at the party: at the same time. That’s superpower is what makes today’s retail fascinating.

Roles within the retail organization have had to adopt and adapt to newer ways of working, and none more so than the roles within marketing. You know, the ones who generate the demand, increase footfalls and visits, engage in conversations, influence a sale, increase basket value, promote loyalty. Those guys. The way they are engaging the customer and enhancing the customer experience has truly gone through a massive overhaul. And the true beneficiary of all this advancement, the customer. Allow me to elaborate.

3 ways marketing in retail has evolved.

Deciding on what promotions to run and how – Grown men dressed as cartoons, people handing out free samples and pamphlets, huge banners offering even bigger discounts – all calling attention to the new cereal brand that a CPG manufacturer launched. Scenes that today’s Marty McFly would see if he went back to the 80s and 90s. Real estate costs have ensured that retailers can no longer afford to have huge promotional activities in-store, but there is a much bigger space out there that offers unlimited space to run promotions, online. Stores now have apps, websites and an ever-increasing following on social media. These are perfect playgrounds for the marketer of today to announce promotions on new product launches, discounts, and offers.

But before one gets there, they must decide what promotions to run. Analytics solutions provide insight into consumer behavior and patterns that allow marketers to decide on a specific segment of their marketable audience a promotion might really work on. Add demand forecasting based on local and seasonal variables to the mix and you know have a better understanding of which offer needs to be promoted. The big players are even accounting for the demand fluctuations based on the weather to ascertain what products need to be promoted. Isn’t that next level stuff?

Digitization of conversations – One salesman for every two aisles. Every customer that lingers on for more than 5 mins gets a ‘hi, how may I help’ you. Great playbook, worked well. Then. Today’s shopper learns about your product, reads reviews for opinions, gets influenced by peers and knows what needs to be bought before they even enter the store. Face to face conversations is no longer the moment of truth. This would mean the overall marketable audience has increased exponentially and the conversations you need to have with every prospect plays a crucial role in increasing awareness and interest in a specific item.

Several tools are now available in the market that let you push mass communications on social, email, mobile and even in-store displays. But the real trick is to stitch a flow that makes it seem like every touchpoint with the customer is crafted per the individual’s lifestyle and appears personalized. This is mainly done by algorithms and the approaches can be broadly categorized into two types.

Collaborative filtering methods are based on collecting and analyzing a large amount of information on users’ behaviors, activities or preferences and predicting what users will like based on their similarity to other users.

Content-based filtering methods are based on a description of the item and a profile of the user’s preferences. Keywords are used to describe the items and a user profile is built to indicate the type of item this user likes. In other words, these algorithms try to recommend items that are similar to those that a user liked in the past (or is examining in the present).

Without these algorithms helping them communicate digitally, a retail marketer today would face a tremendous challenge in having a ‘voice in the market’ and keeping their brand ‘top of mind’.

Omnichannel, real-time communication – The consumer of today no longer sees online and physical stores as two different entities. If your brand must drive loyalty, it must provide a seamless experience online and off. Click and collect, same day delivery and other fulfillment models sure help in the delivery of your products but the bigger challenge is to communicate with your prospect effectively in-store, around the store and online. A marketer now can get a single view of the customer across all the touchpoints and the information no longer resides in silos. Remember the days of last touch attribution?

Location-based analytics can now tell the marketer when the user is near the store and a targeted promotion can be sent based on the users online browsing behavior. In store beaconing technologies have given a serious boost to a marketer’s ability to send relevant offer promos within the store. Old school retailers used to rely on pop up displays, VR and off late, AR too. But consumer preferences clearly indicated that these technologies are not the best usage of time, space and more importantly, money. ‘Tell me if you have what I want, tell me if it can be bought cheaper, and tell me where and how to buy it’ is all the information that today’s consumer needs and the retailers are delivering. AI and prescriptive analytics have further augmented their ability to communicate in a complex omnichannel setting by automating time-consuming tasks like content creation and optimizing spend.

The old school, Don Draper sort of marketer is sure learning how to use tech, and it’s not just the marketer that is benefitting from this evolution, but the customer too. If you are looking for a solution provider that has enabled multiple retailers with the above capabilities, take a look at manthan.com.

4-point plan to launch or optimize a private label

February 9, 2018 6:52 am No Comments February 9, 2018

Intense competition in the retail space has ensured that the customers are spoiled for choices and as a direct result, margins for the retailer has dropped considerably. Imagine a customer walks into the store looking ketchup and sees about 40 assorted brands on the shelves. S/He is most likely to pick the one that has the maximum brand recall, or look for something that is the cheapest or, randomly picks one and drops it in the cart – it’s just pureed, processed tomato pulp after all. Majority of shoppers can be categorized into these three buckets: Loyalist, discount shopper or the impulse shopper and if a retailer is keen on maximizing profits from these profiles, cutting the cost of procuring end products from manufacturers and middlemen would certainly help.

Enter the protagonist: Private Labels

According to a recent study by IRI, private label brand significantly outpaced the industry average growth rate (4.1% to 2.8%). Private label CPG now accounts for over 17% of multi-outlet unit sales and enjoys a nearly 22% unit share in the grocery channel. Seven out of 10 millennials prefer stores that have a wide selection of private label products, and nearly as many (66 percent) often buy private label options over name brands. The appeal isn’t limited to younger shoppers; consumers from all generations view private label as a way to save money and improve value without sacrificing quality.

If you are a retailer and looking to launch your own private label/ optimize profits of your existing label, here’s a 4-point plan to get you kickstarted:

Identify unmet customer needs – No demand, no need to supply. To identify the demand, there are several routes that one can take:

Feedback from store operations on specific items that customers keep enquiring about frequently

That specific item that keeps going out of stock no matter how much of it you stock

Do a market basket analysis of all the items purchased over the last few years to identify maximum SKUs sold

Analyze search trends and patterns on your website and app

Feedback and survey analysis of customer sentiments

Look at competitor labels/ talk to analysts

The foundation for identifying customer needs is, of course, the availability of data and a strong analytics platform that can help you gain insights out of that data. Once you have your analytics in place and reviewed the above items, you have a clear idea about the product line that can be the guinea pig for your private label.

Put your supply chain to work: Traditional supply chain looks at optimizing the supply chain and includes:

liaising with suppliers to eliminate bottlenecks
sourcing strategically to strike a balance between lowest material cost and transportation
implementing just-in-time techniques to optimize manufacturing flow
maintaining the right mix and location of factories and warehouses to serve specific stores
using location allocation, vehicle routing analysis, dynamic programming, and traditional logistics optimization to maximize the efficiency of distribution.

Can you imagine the amount of information that is available with all these ‘external employees’ and your internal teams?

Private label means relationships with industrial and product designers, materials suppliers, factories around the world and logistics providers. And all these ‘new’ relationships are within your arm’s reach. Factor in the analysis you did about customer preferences and you can narrow down on the specifics. For example, with the ketchup example, you learned that the loyalists prefer fresh, organic, no sugar ketchup. Conceptualize the product with your design, category managers, and product teams. Get your team to reach out to factories within a 200-mile radius and link them to organic farmers within the area. Identify optimal routes and logistics to the factory and distribution from factory to stores. Put a production and supply schedule in place based on demand and sales forecasts.

Get the pricing right – Is your target audience a discount shopper or impulse buyer? What are the prices of other products that you are placing right next to this one? What are competitors pricing their private label of similar offerings? There are some top-notch retail solutions out there that aid retailers price your product intelligently by analyzing a variety of factors that impact pricing such as the age of stock, lifecycle stage, inventory count, sell through, demand, competitor price analysis, promotions or bundling. Given that the lifecycle of the product is at a nascent stage, you can, however, take some liberties and take additional factors into consideration further down the lane.

Take your overall costs for that product into consideration, and you’d also want to get a general idea of how that product category is priced. In general, private label products are priced lower than national/ international labels. This is because private label products lack the brand value carried by bigger brands. These brands have earned a reputation and consumers will pay top dollar for that brand value. Private label products have long carried a reputation for being a “cheap” alternative and therefore have weaker brand value.

The key to getting the final price right is to simply let the product present itself to the customer for a set period of time with alternative prices. You can then use algorithms to recommend the optimal price.

Decide Optimal Branded-Private Label Mix: You must get your category managers involved in this biggie. Category Managers can continually optimize the product mix by recommending products to be dropped, retained, replaced or substituted. They can also identify complementary products that can be bundled based on purchase patterns, linkages and cross-sell opportunities.

The other decision you could make is whether to go with an instore heavy/ web/app heavy placement of your product. Capturing web search data will help retailers make that decision — Are customers searching for a brand or features in a specific category on the site?

Retailers must realize though, that adding additional products into an assortment will eventually lead to cannibalization. While you are heavily invested in making your private label work for you, also pay close attention to which brands are getting affected in return and if it’s worth having the other brand on your shelf.

I hope these pointers give you a good head-start in getting your private label strategy right. In summation, consumers are giving retailers permission to grow their private label brands. The real question is will retailers grow private label brand value or simply grow more private labels? You really know that your private label strategy has worked when the discount and impulse shoppers have been converted into loyalists.

If you are looking for solution providers that can help you with your private label strategy, visit: Manthan.com

Counterpunching AmazonGo

January 30, 2018 11:26 am No Comments January 30, 2018

Unless you are living under a rock, you have probably heard of AmazonGo. At the time of writing this article, there were 10M+ views of the video Amazon made to show the world how it’s done. There have been millions of shares on Facebook and Linkedin, and the retweets ensured almost half the world has already seen the ‘future of retail’. For the benefit of the ‘living under the rock’ cohort, here’s how it works:

All you need to get started is an Amazon account, the free Amazon Go app, and a recent-generation iPhone or Android phone. Once you have the AmazonGo app, scan to enter the store and the store recognizes who you are.
Once inside, there will be no store assistants apart from the people baking and making fresh food on counters.
WiFi or Bluetooth LE connections will ensure customer recognition at every aisle.
Proximity sensors and cameras recognize that you have picked up a specific item from the shelf and it is credited to card/cash in your AmazonGo app.
If you put the product back, the item’s cost is deleted from the AmazonGo app and money is debited
You only need to bag the items and exit the store. No checkout lines. Your Amazon account automatically gets charged for what you take out the door.

Jetsons? Scenes from the spaceship in Wall-E? While the tech is surprisingly refreshing, and the experience is novel, the store is currently available in only one location, Seattle. Business Insider reported they had seen internal Amazon documents that described Amazon opening up as many as 2,000 stores, over the next ten years. That’s still not enough stores to cater to every shopper across the civilized world. This gives enough time for the rest of the retail world to catch up and start applying themselves to enriching the shopping experience.

So how does a retailer go about counter punching the AmazonGo phenomenon? Do you need a $10M a year budget to develop labs that can prototype ideas? It’s simpler than you think. Advancements in retail are within the reach of every retailer that is inclined to collect data. Technologies are readily available to stitch a customized, personalized experience to shoppers that would not travel miles to get to the only AmazonGo store in their city. See what I did there?

Here are 5 ideas that can be deployed in supermarkets and convenience stores in less than 2 quarters:

In-store shopper tracking – One of the biggest challenges of shopping at a store is not knowing where your product is shelved. An average shopper spends about 12 mins looking through one aisle to find a product. As a retailer, you might argue that this is time well spent, they get to see all the other products on display. But as a shopper, this is the kind of shoddy experience that AmazonGo feeds on. Indoor positioning systems are now available to identify a shopper when they walk in and beams a virtual map of the store on their mobile device. You can search for the product that you are interested in and the virtual map takes you there, kind of like Google directions.

Digital personalization – While AmazonGo is still testing grounds, Amazon, the virtual store has years of experience in personalizing the digital experience. If you have taken the ‘reverse Amazon plunge’ and started selling online, personalizing your website, app and communications should be your top priority. Recommend best offers and products, recommend products bought together, hot selling products etc based on personas, browsing history and past purchases on your website. You can send geo-relevant offers, best offer set, shopping and wish list based offers through your app. Dynamically present offer and content on newsletters, through a recommendation engine, using customer attributes such as home-store and lifestyle.

Customer-centric assortments – Imagine the amount of data crunch that is being done behind the scenes of AmazonGo to ensure that the right product is available when the customer walks in. They have to get it right, there is no one to talk to and ask for the availability anyway. Your Category Managers can now continually optimize the product mix by recommending products to be dropped, retained, replaced or substituted. They can also identify complementary products that can be bundled based on purchase patterns, linkages and cross-sell opportunities. Additionally, there are now solutions that can recommend appropriate price points for products that are slow movers based on external factors and internal data. Use all these data to ensure you are carrying the right assortments and you never have an out of stock event in your store, ever.

Real-time inventory insights – This one’s a biggie. This by far is the single biggest challenge that daunts any retailer and should be the first bullet on your 2018 wish list. Solutions now provide real-time information of potential out of stock situations and trigger purchase orders for stock, all automated. The other ‘simple fix’ is to trigger automated intra-store transfers for stock replenishment. Couple this with a solution that recommends markdowns for excess inventory and streamlines the overall buying process, and you are already making millions, by cutting your losses.

Democratizing insights to store managers through mobile apps – While walking through a store without any human interaction and picking up your item and leaving the store might seem exciting the first few times, I think what makes shopping in-store appealing, are the interactions themselves. The biggest challenge in getting the store managers and associates to deliver at the moment of truth is lack of data and insights about the customer. They need to know what is relevant to them at the right time and medium. Communicating complex insights and information through emails is passé. Insights need to be communicated to the store operations team, comprising solely of millennials these days, through their mobiles and apps. They need to have access on-the-go and not have to go to a laptop/ desktop placed at a part of the store with the least footfall.

I hope these pointers give you a head start in counterpunching the giant. If you are looking for a solution provider that has enabled multiple retailers with the above capabilities, take a look at manthan.com.

A Day In The Store – A Bedtime Story for Retail Store Operations

January 22, 2018 11:24 am No Comments January 22, 2018

Charlie’s factory was a multi-million dollar store with toys that all the grown-ups seemed to love.
They had a million registered repeat customers transacting with them every month and they brought in close to 55% of their monies.
Using an analytics tool, their leader Chuck and their little IT elf John managed to build an awesome model on behavioral segments of customers. Their output was 6 clusters with varied behavior.
They built a beautiful promotion strategy for different segments and executed them.

Their best customer, Alice walked into the store with that “Exclusive” promotion that she received, with a bunny in tow of course. Chuck had strategized to retain this customer as she was a very valuable one. But Little Tommy from the operations team wasn’t aware of this and the cashier, Ronda or store associate Tim, disregarded the “Exclusive” promotion. Poor Alice was disappointed with the treatment she was given at the store and the bunny…? He took out the Duracell batteries from his behind and chucked it at Tim, vowing never to buy at Charlie’s factory again!

Moral of the story: Analytics becomes a success story in your organization only when it is executed in a unified and aligned manner, right from the start to the end. Else, you are probably wasting your marketing money and analytics efforts, and worse, your customer’s loyalty.

Here is how you can fix this: Start empowering your store operations team. They need to know what is relevant to them at the right time and medium. Communicating such complex insights and information through emails is passé and you lose valuable time. All these info needs to be communicated to the store operations team, comprising solely of millennials these days, through their mobiles and apps.

To empower your Store operations team, visit Engage247 website.

Amazon vs Rest of the World

December 26, 2017 11:06 am No Comments December 26, 2017

Amazon has 536 Million Products on sale as of now. Not SKUs, products.

Let me put that in context. If Amazon wanted to, it can give one unique product to every single person in all of North America as a Christmas gift and still have the same products on its virtual shelf for the rest of the world to buy.

Isn’t that mind-boggling?

People are now searching for ‘stuff’ on Amazon directly because they know that Amazon’s endless aisles are sure to have the product they are looking for (This ‘searching on Amazon’ phenomenon has other players like Google worried, but more on that, in another article). How does a retailer, specifically the ones who deal with individual categories resist getting steamrolled by this Goliath?

You can never beat Amazon in Assortment volume, but here are some actions you could take to challenge the Goliath.

Drive real-time engagement:

Treat every guest context such as restaurant visit, cart composition, promotion response, coupon burn, e-commerce clicks, etc. as a dynamic trigger for personalization. Intelligently and uniquely respond to every guest with next best offer based on past behavior, like-for-like patterns, and marketing priorities.

Smarter Category Management:

Localize assortments based on sales forecast, customer demographics, purchase patterns, weather data and seasonal trends.

Plan Assortments better:

Identify fast moving, slow moving, overstocked and understocked items to help identify the right assortment for the next season.

Optimize Markdowns:

Analyze historical category and brand performance, market trends to recognize markdown performance and leverage those insights to design effective markdown campaigns.

Democratize Store Insights:

Arm store managers, department managers and associates with necessary insights about sales, promotions, inventory and employee productivity.

Boost fulfillment performance:

Identify the bottlenecks in shipping delays and ensure better customer satisfaction by making smarter vendor selections.

Clienteling

Enable store associates to initiate conversations with high-value customers based on their personas, past purchases, and next best offer.

Win back Lapsed customers:

Identify guests who have lapsed or at risk of leaving and proactively take actions by identifying the right mix of offers and channel strategies to engage them.

If you are interested in seeing some real-life examples of how other retailers are combating Amazon with innovative store experience ideas, Download this Whitepaper

6 ways AI is helping retailers in real life

December 14, 2017 6:32 am No Comments December 14, 2017

When E-commerce took off the way it did, every retail pundit predicted the doom of in-store shopping as we knew it. The novelty and glamour associated with in-store shopping were replaced by convenience and never-ending aisles that an e-tailer brought. These ‘new guys’ were born and brought up in the tech industry and knew how to use data to make products more accessible to customers. But, things always don’t go as planned, do they? The hostile takeover of the retail kingdom is getting harder and as it stands today, the e-commerce players market share is still in single digits. The fightback has a lot to do with, surprise surprise, technology helping the physical stores. The laggards are learning and learning fast. If you look at the employee break up of the ‘new age store owner’, you will start seeing more analysts, data scientists, and digital innovation roles than the erstwhile, store help/ associates. This truly is the make or break period for the physical store owners and they are going all out in adopting modern technologies to counter the ‘born with data’ e-com frenemies.

So, who’s helping them?

Technology companies that offer both, technology services and products. They have created entire ‘retail-specific platforms’ to make the transition easy. For the novice store owner, something like a data visualization tool that offers colorful graphs might look really appealing and they go all out in acquiring an enterprise BI solution. But the more experienced and thoughtful ones are turning to much more advanced tech like AI, machine learning, and prescriptive analytics to truly operate at scale.

Today, AI is no longer a concept that has limited use-cases. The leading product companies are showing the way by applying AI in real life and retailers are gobbling it all up. Here are 6 ways retailers are using AI in their day to day operations:

Stores are using AI to automate real-time store engagements through apps
AI is now helping retailers by prescribing customer-centric assortments that are more likely to drive higher store sales in a specific location.
Merchandisers and Category Managers are using AI to decide on price-offs and promotions for every SKU
AI is also being used to recommend personalized, next best offers for individual customers
Channel optimization is the latest of the lot. AI is being used to identify the right channel to target a specific customer
Store managers are using AI to predict out of shelf and out of stock events to take corrective replenishment actions

If you are interested to learn get a demo of how all this is done, ask Manthan . Or better still, if you are visiting NRF 18, set up a meeting with the team here

The year 2018: Predictions for Convenience Stores

December 1, 2017 11:26 am No Comments December 1, 2017

As the convenience stores segment goes through yet another year of evolution, catering to the new ‘I need everything personalized’ customer is clearly standing out as the biggest differentiator from the competition. To take it further, here are top three trends that are clearly standing out.

Convenience chains are increasingly turning to predictive and prescriptive analytics to make automated decisions that are based on data
Merchandisers and store managers are being empowered to make decisions on the go
Customers are expecting personalization and as a result, brands are doubling down on digital customer engagement

To maximize revenue impact and be prepared for 2018, C-Stores have 5 levers that they can use to be successful.

Have a system that can prescribe profitable and timely decisions for merchandising and store managers about assortment, inventory, pricing, promotions and day-to-day store operations
Empower marketers to identify revenue generation opportunities and predict customer behavior by understanding customer behavior and preferences
Improve customer engagement by executing machine learning based personalized promotions in real time across email, SMS, mobile app and social
Create a high performing agile supplier network through comprehensive insights, process automation, and data integration between the retailer and suppliers
Implement local pricing strategies across stores based on competitor pricing and customer segment needs

To know more about our Convenience Store Solution, Click here to Download

Manthan and Computer World Partnership in MEA – An interview

October 11, 2017 10:41 am No Comments October 11, 2017

Samantha: We have been reading about the Manthan and Computer World Partnership in a lot of places, can you tell us what this partnership brings to the market?

Ehtesham: Retailers in MEA need the right industry focused analytics solution to face the current business challenges and operate profitably. And key to this is the mining of insights within their data. Its appropriately said these days, that Data is the new Oil!

Manthan Analytics solutions are purpose built, industry focused, aggressively priced and quick to deploy. And through our partnership with Computer World, we intend to leverage the extensive reach of our partner, to bring our award-winning solution set to the regional clients in Saudi and Bahrain.

Samantha: Can you tell us about the work that Manthan has been doing in MEA in recent times and the opportunity you see here?

Ehtesham: Manthan Middle East has seen a phenomenal growth recently of over 65% YoY in revenue, increased clientele count by over four folds and acquired like-minded partners in over 30 regional countries representing us. All this in the so called ‘challenging environment’.

A lot of our existing customers are seeing tremendous value from the solutions we have delivered. I recently met with one of our top customers in the region and they wouldn’t stop thanking us for ‘putting their data to work’. I see a lot of retailers in the region still using a standard, run of the mill ‘excel-ytics’ or generic and basic BI solution that does not fit the need of a retail industry. They end up spending a lot more money on acquiring more tools and complementary solutions to make up for the lack of decision enabling insights. But all this can be accomplished with our retail specific solutions and we hope to bring this to MEA, in a big way.

Samantha: Final words for a prospect that might be reading this?

Ehtesham: Instead of investing in new transactional systems or complicated non-purpose built BI or Analytics applications, you should be leveraging the powerful insights within your own data, and do that quickly, to get/keep your businesses on track.

Contact Ehtesham

State Of Customer Experience Today

September 15, 2017 9:38 am No Comments September 15, 2017

The retail customer experience has seen a radical shift in the past 5 years. The values attached to better experiences have started to surpass discount incentives offered. Customers have become more digitally aware of what product they are looking for, more expressive and perceptive about product feedbacks, as well as more appreciative and savvy at getting adept at in-store technology initiatives taken to smoothen their purchasing experience. Such initiatives also automatically associate a level of trust on quality of the product offered.

Some of the Orthodox in-store practices have started to take a toll on customer shopping experience. A confused or furious customer staring at length with wrinkled forehead lines is a guiding path of where the need for innovation is more daunting. The most significant concerns baffling a customer is:

I always end up spending more time in the queue than I do purchasing, Should I be more productive and fire up the app to play Pokémon-go in the meanwhile
Always the same customer registration form, why can’t I register with a click on an app?
Wait, how much loyalty points do I have, in my wallet?
I like to give feedback, but why fill the same form again and again?
Why can’t I search and compare the product in an App or see the review?
I must have burnt a few extra pounds, just trying the several trouser options, where can I find some water?
Holy Christ, I have eight coupons from the newspaper cutlet and ten products in my basket, which gets mapped to what, do I score an ‘A’ grade if I get the combination right?

Modern retailers have embarked on several such initiatives aimed at reducing friction for every point of the shopping journey. Cashier-less stores: the largest retailer in Singapore has advanced on this bold initiative to counter the problem of long queues. Their stores now have self-check-out counters for users to scan and bill their products, without any personal assistance. The store also provides a device for the customers to scan their products while purchasing. Once a user is done with the purchase, he/she attaches the device back on the self-checkout counter and pay for his basket. This has reduced the length of shopping queues significantly.

A mobile application is a one place stop for many such in-store problems. A store map integrated within the app can help the user to find the location of products. The same interface can provide user to compare multiple products based on product or rating specs. A user can be provided notification based on his shopping preferences or can be nudged back to come in store if he hasn’t been to the store for a while.

Brand shopping mobile applications coupled with smart lightings have helped track customer movement within a store. A journey can be traced to identify which sections appeal most to a customer: such insight presents tremendous business opportunities for better profiling customer behavior. This has opened the floodgates of data collection to track and understand window shopping behavior and apply vis-à-vis e-commerce driven marketing strategies to in-store behavior. Now a user can be notified about information on an associated product within the store before he has even made a purchase.

The boom of e-commerce shopping experience has put an immense pressure on retailers of all form to focus on horizons beyond in-store experience. Web-influenced offline sales topped purely offline sale for the first time in 2016 – totaling to $1.6 trillion and is expected to grow by 12% through 2018. Customer’s in-store purchases have been impacted by their offline perception before being bought. Online purchase behavior suffers from a trust gap between the actual and perceived product value with experience, while offline purchases are hindered by the ease and inability to evaluate quality specs and product reviews. Thus, there is a need to provide a consistent experience between online and offline modes. Such an experience will help to bridge the trust gap and minimize the confusion caused by exposing a customer to several unsuitable variants of a product. Retailers need a platform to integrate and generate a single view of customers across his range of behavior across social, e-commerce, online and loyalty data for better understanding their customer preferences. A common concern echoed by most retailers is that their outdated technology infrastructure restricts them from adopting a unified platform solution. Off course the technology shift requires a definite investment. The executive leadership must take a call whether to ride with the rising tide now or come onboard later just to see other competitors flaunting their honors past the finish line. The inertia to shift from existing technology infrastructure will be a key differentiator for a digitally successful retailer.

If you are looking for ideas to improve your store experience, Manthan can help you. Manthan’s Retail Analytics solutions are built exclusively for retail and tailored to fit unique retail decision-making needs. With the experience of serving 100s of customers across 22 countries, across Fashion & Apparel, Food & Grocery, Specialty and Mass Merchandise, you are bound to get what you are looking for.

For a quick overview download this Datasheet

If you are interested in a 15 min. discover call with Manthan, do write to us at online.enquiries@manthan.com

Fair Price & Importance of Customer Location

September 14, 2017 11:30 am No Comments September 14, 2017

The location has always been an important factor in retail. It is gaining an all new meaning with retailers detecting customer location inside the store and offering range of services to make their trip more enjoyable and engaging.

Largest supermarket in Singapore is working on an innovative indoor positioning system which can detect customer location within a store. Indoor positioning will enable the retailer to enhance the shopping experience with wayfinding capabilities and in-store promotions delivered in real time on customer mobile phones. Customers can receive optimized in-store directions to products saved in their shopping list, receive contextual & location-based personalized notifications making customers aware of best details exclusively available for them.

For long, online retailers have been at an advantage of knowing their customer’s journey and being able to offer personalized experience along their path to purchase. In-store positioning promises to bring Brick and mortar retailers at par with online retailers. The technology seamlessly integrates mobile apps and physical stores to deliver a personalized experience to customers currently restricted to only the online channels.

For a detailed understanding of this deployment, download this case study