Wednesday, 27 February 2019

3 Things Every Retail Marketer Needs

Retail Marketing today is shifting from understanding what the customer wants and providing them with it, towards being a trusted advisor who adds value to their life. Imagine how pleasantly surprised a shopper would be if she came across that perfect stole she wasn’t even actively looking for.



But to enable such experiences for customers, retailers need an army of staff who are studying customer behaviour, preferences and activity all the time. Alternatively, this can be done seamlessly with data science. Artificial Intelligence and advanced analytics are pushing the boundaries of what is possible, equipping retailers to become truly customer-centric.

The More Things Change…


The last two decades have clearly demonstrated that the fundamentals of marketing remain the same businesses that are able to consistently delight customers are the ones that succeed. What’s changed are the mechanisms used to achieve this. Pre-digitization, communications were one-way through mass media and only touchpoint was at the physical store.
Since shoppers now consume information differently and through multiple channels, marketers are changing as well. 


When it comes to campaign management, these 3 things that are a must for marketers:



Seamlessly Connecting Channels for a Consistent Experience: Managing customer interactions across channels come across as a basic requirement, but to do this, marketers need to make sure channels and devices converge to offer a meaningful experience. This requires not just a customer data platform, but also a campaign management solution that is truly omnichannel.

Predicting Customer Behaviour and Activating Personalization: 


With segmentation, marketers can understand customers and their preferences. What differentiates a leader is their ability to predict behaviours, and activate those insights such that customers experience one-to-one personalization like they did with their friendly neighbourhood store owner. AI-based personalization is not limited to just basic variables such as gender and age but uses deeper insights such as the individual’s lifestyle, the image they want to portray, how much they value exclusivity versus discounts, their life-cycle stage, and more.

Communicating with Customers in Real-Time: 


For retailers, being able to act on customer micro-moments is critical to positively impact conversion. This is where an in-depth understanding of customer journeys come into play. If a shopper was browsing for a product but did not purchase, it is easier to nudge them towards a purchase with a timely notification or offering. Mobile in-app and push notifications are becoming increasingly important for engagement – it is real-time, easy to consume, and does not encounter the friction of channels such as e-mail.

The Right Campaign Management Solution Does the Heavy Lifting:


The value proposition of data-driven marketing has changed. Earlier, data was used for reporting,  creating dashboards and keeping tabs of spend and revenues. Today, data is used to generate prescriptions and recommendations, so that you get the best returns from marketing while maximizing customer lifetime value.
This is the new era where only what needs attention gets highlighted, and best actions are suggested. The heavy lifting of data aggregation, insight generation and simulation take place behind the scenes.
A truly advanced campaign management solution can listen to customer behaviour and execute personalization in real-time.

Mobile app based customer targeting: 


The right solution should enable marketers to easily target customers who have downloaded a mobile app but not registered. Or even customers who have registered, but not purchased or haven’t interacted with the app in a few weeks. This can be highly impactful with the addition of rich media notifications and in-app personalization of banners and coupon wallets.

Location proximity-based marketing: 


Knowing when your customers are near can offer a tremendous advantage. Being able to send promotions to customers, based on their past purchase history, when they are nearby or inside your store, can draw them to make more purchases. For example, a customer in the golf shoe aisle might be interested in a bundling promotion you are running for golf tees.

Intelligent journey builder: 


Drip campaigns and sequential promotions can extend journeys using customer’s response on a channel or can be based on predictive micro-segmentation. Communications that are customised (aspects of when to send, what offer to send, and what channel to send on) to live user activity have a higher conversion rate. For example, events such as mobile app launch, cart updates, or even inactivity can be used to tailor the next communication, and move customers towards a purchase.

Test and Experiment within journeys: 


It’s hard to know upfront what channel, what time and what combination of copy, offer and creative treatment will have the maximum impact. With A/B testing, marketers can easily assess the performance of each component and arrive at the best arrangements. Similarly, test and control is a great way to measure the effectiveness of a new tactic.

A New Era of Delivering Experiences at Scale:


Technology is evolving to make interactions contextually relevant to customers. By working with online and offline data (including POS, mobile, text messaging, e-commerce and email), artificial intelligence can manage it all, at scale, in a quick timeframe for tens of millions of customers.
And retail marketers who do this well will be able to form deeper relationships, enhance customer engagement and loyalty and retain their best customers to impact growth.

Sunday, 17 February 2019

Food and Grocery Analytics – The New Age Realities


Food and Grocery Retail is one of the fastest growing segments and as per an estimate, by 2022 consumers could be spending $100 Billion on online grocery alone, constituting more than 20% of the overall market, worth almost $ 1.5 trillion. While there is a dip in disposable income of an average citizen, the daily bread and meat is not something she can cut down on. Retailers must build their strategy keeping her in focus, giving her the seamless and intuitive shopping experience, she desires.


This is in line with what Gartner suggests, it is vital to reorganize Food and Grocery analytics around the needs of the consumer. But it is easier said than done. According to a study by FMI and Nielsen – many retailers are not prepared to meet the needs of omnichannel food shoppers, not for lack of multichannel assets or touchpoints, but for want of cohesive strategy integrating the physical stores and online business processes. They are struggling with fragmented data and are “failing to adequately share shopper data, segmentation and other consumer insights leading to missed opportunities”, the report claims.
Poor forecasting ability also hinders scalability for the retailers. Most retailers find it challenging to strike a balance between demand planning and response execution and fail to reach the right customer at the right time with the right offer. Their marketing promotions are still following the traditional product-centric strategies rather than being aligned to customer choice and preference. The new age realities are making the hitherto followed strategies and processes redundant. In today’s world, the shopper is being lured with sophisticated technologies that not only recognize them as individuals, pre-empt their shopping needs, but also help them plan their shopping and make most of the prevailing offers. 

How do the average Food and Grocery retailers keep pace with such sophistication? What should they do if they have to survive and thrive in the omnichannel world and make their storefront an attraction for the customer to pay repeat visits? How can they come closer to the customer and re-imagine their entire business by keeping the customer in the focus – be it merchandise, inventory, store operations or marketing? Further, how can they empower the teams on the shop floor with insights and prescriptive actions to deliver unique experiences to the customer and ensure the suppliers are always replenishing the right shelves with the right assortment? Here is some essential and effective retail analytics solution for food industry which retailers can adopt in building the F&G store for the connected shopper by reimagining the systems for store operations, supplier collaboration, trade promotions, and marketing campaigns. 

4 Ways How Restaurant Analytics Can Make Your Business More Profitable


As a restaurateur, you probably know that you are in a highly competitive industry. Hundreds of restaurants open every year, but not many succeed in remaining open. According to Modern Restaurant Management, a leading US-based magazine that covers restaurant industry news, 50,000 restaurants shut down their business every year in the U.S. The situation is not significantly different in India. So what can you do to ensure that your restaurant not only remains open but grows profitable too? The answer is simple – embrace restaurant data analytics solutions.  
Image result for restaurant analytics manthan



Restaurant analytics will analyze your restaurant’s data and decipher what ticks your customers off and what makes them happy to help you understand and fulfill their expectations, so that they prefer your restaurant to your competitor’s establishment. Here are four ways how restaurant data analytics can help you run a profitable restaurant business.
1.    Creates customer segments
Different kinds of customers are motivated by different factors. Restaurant analytics analyzes customer behavior to classify them into different segments and help you create special offers to attract them. For instance, a family of four visits your establishment every weekend, and orders items within a particular price range. Data analytics can identify customers with similar attributes and create a separate segment of such customers. You can now devise engagement strategies like special discounts on some items or a separate menu to earn their loyalty.
2.    Enhances menu offerings
Nothing attracts customers more than a meticulously designed and strategically priced menu. By analyzing consumption data, restaurant analytics can identify the best sellers and the dishes that have a few takers. This will help you adjust the pricing according to the demand, execute a well-planned menu, and also modify it according to the seasonal availability of ingredients. 

3.    Helps you overcome shortcomings
To run a successful restaurant, you must always strive to improve the customer experience. By analyzing data, restaurant analytics can uncover the gaps in the dining experience and help you rectify the shortcomings. For instance, if data analysis  reveals that the long order waiting time is putting your customers off, you can hire more staff to resolve the issue.
4.    Identifies new opportunities
Restaurant predictive analytics can identify new opportunities and help you act on them. Let’s say, with the help of data analytics you discover that the number of customers ordering food online through your website has increased significantly. You can give your online patrons a smoother online ordering experience by tying up with food delivery companies that have become quite popular these days. It will also improve your digital presence which means more customers and increased profits.

In short, from helping you read the pulse of your customers to improving operational efficiencies, restaurant analytics solutions go a long way in transforming your restaurant business to a more profitable one. If you are looking for such a solution, get in touch with Manthan . We specialize in designing AI-powered analytics applications for customer-facing businesses.