An optimal menu not only drives financial success but also enhances guest experiences. This makes Menu Engineering a key aspect of QSR strategy. With real-time insights, Operations Leaders could engineer their QSR menu to keep costs under check while ensuring customers’ favorites are firmly placed in the menu.

 

Personalized menu with advanced customer insights

The sudden spike in online ordering through apps presents immense opportunity for QSRs to hyper-personalize customer experience. And menu personalization is a key element of the overall experience. Data on customers’ taste and preferences are collected and analyzed. Using machine learning and AI technology, the app shows users the most relevant menu items, promotions and content based on their individual preferences, past dining history, location, weather and restaurant specific menus and pricing.

With data and intelligence, menu engineering is more science than art, in today’s times. An advanced AI platform helps you engineer your menu across outlets, reduce cost and drive loyalty. The underlying need to design optimized menus is Data – menu items, number sold, food cost, menu price. Clean and structured data on your customers, likes, preferences, transactions, affordability, menu items and their costs are some of the key inputs to the menu formula. 

Advanced algorithms analyze the demand and costs of menu items to help you identify your most and least profitable menu items. AI platforms integrate with back-of-house systems to draw this data and throw up in-depth intelligence to help make smart decisions on menu and other aspects of QSR business. 

An advanced BI and Restaurant Analytics platform provides real-time insights to re-engineer your menu, forecast sales, reconcile 3^rd party sales, optimize delivery time and more.

Let AI help you identify your Stars on the menu

Manual menu analysis is bereft of inaccuracies and never complete. This leads to loss of revenue opportunities and impacts profitability. As alluded to earlier, data and intelligence could help identify popular menu items across stores and locations in real-time. Advanced algorithms map trends, cull out underlying reasons and recommend next best actions for menu items. For e.g., Algorithms throw up the bestselling pizza by size, day, topping, location and recommend menu combos that would help you leverage its popularity. 

By adding data on item cost and profitability to sales of menu items, you can be sure to accurately identify the best and worst performing items, from your long menu list.  Using this, QSRs could develop an action plan to optimize the menu by reducing low profitability items and increasing the popular ones. 

Menu engineering is about managing this mix of stars, plow horses, dogs and puzzles that leads to reduced costs, improved profitability without compromising on customers’ wants. Let’s see how algorithms could help in arriving at the right menu mix.

Make your STARS shine brighter

Algorithms identify Star menu items based on factors such as sales volume, costs, price, margins, promotions, etc. They help you analyze the underlying reason and recommend ways to make the most of these popular and profitable items on your menu. AI platforms recommend:

• Other locations where these items can be introduced to enhance revenue opportunity
• Price increase by calculating the likely impact on demand
• Menu combos with other items that are lower in profitability, using association mining

Let your PLOW HORSES gallup

Algorithms are quick at identifying items that are growing in popularity. Juxtapose this data against its costs and you know whether you are heading towards the left of the balance sheet or the right. Trust the AI to do the magic – menu combos that offsets the low profitability of the item or more dishes with high priced ingredients for economies of scale. You may just end up with Star with AI-based recommendations.   

AI solves the PUZZLE

With a 360-degree view of sales, marketing & operations data, AI platforms turn into Sherlock Holmes to find that missing piece of the puzzle. Run the analysis and in a matter of seconds you’ll know why they are not flying off the shelf. Turn the recommendation engine on to increase their demand. Reduce price, introduce an offer or run a campaign, these algorithms have a marketing trick up their sleeve. 

Let the DOGS take a walk

While the algorithms are quick at identifying Dogs and recommending their expulsion, human intelligence needs to prevail here. For e.g., Kids’ menu is neither high volume nor highly profitable ut you may want it to stay on the menu. 

Optimize QSR menu with Algorithms

Data and Intelligence are the key ingredients in dishing out a menu with the right mix of Stars, Plow horses, Puzzles and Dogs. Advanced AI tells you what’s popular and why. Likewise, it helps you understand the implications of cost and pricing. And this is a dynamic exercise as customer tastes and preferences, economic and social situation, change. With real-time access to data & insights, AI platforms help you balance high and low food costs to garner a reasonable amount of profit margin yet cater to customers’ preferences. 

Across the world, we are seeing the issues in a fragile supply chain being exposed, specifically in Grocery & Pharmacy segments as they fall into the essential category and seek faster replenishments.

Today’s crisis scenario has resulted in 40% of retailer members of the National Retail Federation to say that they are experiencing supply chain disruptions due to the coronavirus, with an additional 26% expecting to experience disruptions.

The Lean Supply Chain is Now Anorexic

Grocery retailers have in the past few decades, made their supply chains lean, in a model similar to the automobile industry. As a result, grocery retailers have been minimizing inventory, and delivering “just-in-time” products to shelves, as soon as a product is purchased.

The advantages of adopting this were lower inventory carrying costs, minimal product handling and the need for less storage space. But the downside, being experienced by the world today is that unforeseen surges leave stores in a quandary as inventory is not readily available.

Is Technology the Cure?

Supply chain resilience requires retailers to invest in technologies that offer greater clarity into understanding what goes on within the supply chain. Additionally, retailers such as grocers or pharmacy need to have contingency plans to anticipate shortages created by demand surges or supply disruptions.

Today’s supply chain challenges are multiple according to a Digital Commerce 360 survey of over 300 retailers in mid-March. Supply chain communication topped the list (48%) of actions they’re taking as a result of the coronavirus. Others are contingency planning (34%), hoping to minimize disruptions (32%), monitoring the coronavirus situation in China (23%) and working with their partners to mitigate supply chain risks (22%).

More recently many of the larger retailers have been investing more in supply chain technology in order to reduce forecasting errors, track assets accurately and improve order accuracy.

A report by GEODIS found that only 6% of companies surveyed worldwide had achieved full visibility into the companies that make up the sub-tiers of their supply chain. The complexity we have today makes mapping simultaneously more costly and time-consuming, though it is increasing its importance and beneficial insights.

Let’s look at some of the ways, technology is helping retailers overcome the supply chain gaps during the COVID-19 crisis.

Advanced Collaboration Platforms

Better collaboration with vendors through connected systems can lead to an overall improvement in supply chain resilience. Supply chain collaboration platforms can make it easy to reduce the time spent shipping, receiving, tracking, and compiling order data. When combined with collaborative features and analytics, retailers will find it easier to optimize supply chain efficiencies while mitigating risks.

Integrated Portals for Real-time Information

Real-time data is helping retailers manage their supply chain decisions and be able to focus on the movement of essentials. A survey conducted by the Retail Systems Research in March 2020 amongst qualified retail respondents showcases that 76% of retail winners believe that real-time visibility remains an underlying driver of supply chain performance.

Real-time information can be shared by integrating suppliers on a web-based portal. By using a platform to offer end-to-end visibility, all the stakeholders in the supply chain can have the visibility of on-hand inventory and of changes in product demand. 

Expand Supplier Networks Faster

To be able to handle the shortage situation, retailers today have been seeking out more suppliers. But traditionally on-boarding new suppliers and products is a time-consuming process.

Increased global disruption often demands faster decision making. To solve this issue, technology can help create centralized, web-enabled repositories of suppliers, which retailers can access. Suppliers who are up and running can list their catalogues, allowing retailers to locate and identify which suppliers they can work with faster.

The Retail Systems Research reports that the top opportunity for retail success is to improve their forecasting capabilities, along with improving compliance from suppliers. Intelligent search tools and regulatory compliance can be pre-checked when the supplier lists themselves, saving tremendous time and duplication of effort by every retailer the supplier connects with.

Replenishment Automation

A report by McKinsey predicts that automation could accelerate the productivity of the global economy by between 0.8% and 1.4% of global GDP annually. In other words, supply chain automation is both cost-effective and leads to higher profitability.

Enabling integrated systems can offer retailers the ability to assess and automate which key supply chain processes can be automated. With the right supply chain solution, retailers can enable a seamless operation, which then helps automate activities such as inventory replenishment.

CONCLUSION

The World Trade Organization expects that global trading will fall by between 13% and 32% during 2020, and almost all regions will experience double-digit declines in trade volumes this year due to the pandemic.

The ability to adapt responsively to this reverberating disruption in the supply chain operations will truly separate the winners from the losers during the COVID-19 crisis. Whether grocers and pharmacy companies use this crisis as a wake-up call, remains to be seen.

Download to learn more

While the COVID pandemic has amplified the many challenges that plague the Supply chain across industries, it has also brought to light the resilience and innovation to help alleviate some of these.

Retailers across segment were most hit, but they also had to bounce back the fastest and continue to serve the community. One such company is Prince retail, which recently celebrated its 30^th anniversary during April this year. Present mostly in semi- urban and rural areas across all major islands and regions in the Philippines.

We had a chance to interact with Rina Janine Sy Go, Supply chain director at Prince retail on how they have been rethinking their supply chain approach in the face of this crisis.

 

How has the COVID-19 situation impacted Prince Retail Group and the grocery industry at large?

The COVID-19 situation has largely impacted the entire grocery industry when the demand for food and basic commodities increased and supply could not cope up with the demand. Due to panic buying that followed once the lockdown was announced, we were grossly unprepared to handle the demand and the immediate restrictions that were imposed overnight.

Even today, we are largely struggling with our supply chain as vendors are battling with the non-availability of stock due to restrictions in the mobility of their workforce and scarcity of raw materials. Our workforce is faced with challenges while working in our stores and distribution centres. Even our order to payment processes to support the stores were not equipped to support the immediate work from home requirement. It was like fast-tracking our 2-year roadmap for digital transformation strategies to 2 days.

Currently, we are still struggling with the entire operations while trying to sustain availability in our stores. Although it was through this crisis that we really saw the impact we have on the communities we serve. Since our stores are mostly located in rural and far-flung provinces, we were literally the only source of supply that had relatively complete and stable stocks that could feed these communities who were unable to travel to the closest urban cities due to mobility restrictions.

It truly made our mission of “Serving the underserved” very evident. 

 

What was the first response to ensure Business Continuity (BCP) at Prince Retail?

At Prince retail, we believe in being proactive and wear our customers hat and come up with solutions which serve their needs. However, this pandemic is unprecedented and needed out of the box thinking from day 1. Our immediate response was to map the entire supply chain process from order to payment as this was the process and functionality that needed to be available during lockdown.

Together with our leaders in IT, HR, Logistics, and the functional teams, we had to ensure all these processes continue to be available during work from home, so we came up with ad-hoc solutions.

By contacting our telco provider, procuring as many laptops as we could and finding creative ways to get connectivity to the homes of our teams.

We also had our company bus pick-up and drop-off select employees who had no means of transportation.

The store operations team did the mapping of the workforce homes so they could still be available in the stores and if they could not, we find back-up workforce and set up staff houses for employees in critical roles.

It was basically a series of quick and iterative decision-making sessions between key leaders in the organization to set up the whole thing overnight. It involved a lot of cooperation, quick thinking, creative planning, and flexibility from everyone involved.

 

Innovation is the need of the hour and with limited resources in the current crisis what are some of the ways you are addressing it? 

With finite resources coupled with restrictions, innovation was the only rescue. We streamlined the SKU's and vendors so we would prioritize our ordering to cope with the new way of working during lockdown, all this while supporting over 60 stores across the country in remote areas. We could not continue with all the business as usual SKU’s and focused only on the ones driving high demand.

We set up communication lines and chat groups for each team involved to ensure the right problems were being addressed immediately – and connected straight to the top management. We also set up new store processes to deliver directly to our customers who would SMS, email, use Facebook messenger or call in with their orders.

We grouped the deliveries by zone depending on their residential areas to streamline deliveries. This was something that we had never done before but we set up this entire process of working from delivery to payment in just 2 days.

We had to think of making our existing processes flexible and adjust to working in these new conditions so we can continue to serve the community.

 

Based on your learnings on the COVID-19 pandemic so far, what can grocery retailers do to improve their proactive response in scenarios such as these in future?

As Mr. Winston Churchill said once “Never let a good crisis go to waste”, retailers across the globe will use this crisis as a learning to prepare better for future. Retailers should be able to have more flexibility, mobility and redundant resources that can enable the entire supply chain and payment workforce to work from home or remotely, rather than being entirely dependent on the head office physical structure. This was our major learning and pain point.

Digital transformation should have been now rather than later. Retailers should also have higher inventory covers of basic commodities which worked for us because historically, we always carry large inventories of these goods due to the remote locations of our stores and this actually worked to our advantage when we were hit by the crisis.

Retailers should also be ready with an e-commerce strategy and we were lucky since we were already doing pilot runs of a B2B application in 1 store, that we are currently fast-tracking now to allow B2C as well (doing data cleansing, application preparation, technical fixes), and a quick roll out to stores once the crisis is over.

 

Do you see any consumer behavioral changes for–good post the crisis?

These are some consumer behaviours that will change for good especially in the Philippines and with our market in the lower socio – economic bracket. We see a shift in demand for bigger packs and more savings rather than the traditional sachet economy due to reduced frequency of purchase. We also are seeing the acceptance of digital processes for ordering, getting information, and servicing, which means more digital marketing for us as well. We also forecast a bigger importance on health and sanitation. These are SKU's which were previously not a priority especially for our market. There are also changes in how consumers will be choosing their products, brands they pick based on whatever is available at the store level, and preference for more value for money products with a global recession already underway.

Just like Prince Retail collaborated for continuity to defeat disruption, your organization can too. Click to learn how

In March 2020, the Institute for Supply Management (ISM) conducted a survey that focused on the impact of coronavirus disease (COVID-19) on supply chains. Nearly 75% percent of companies reported supply chain disruptions.

The unprecedented outbreak has caused many businesses to experience multiple challenges including shifting customer demand, transport restrictions, shortages, and more.

According to Food Navigator, Nestlé CEO Mark Schneider warns that the business must ‘get ready for the storm’ as supply chain challenges are expected to intensify.

Let’s take a look at some of the new challenges that COVID-19 has placed on retail supply chains:

Digital Collaboration and Supplier Communication

Collaboration and communication can enable transparency and faster responses to operational decisions on both sides. But retailers have often lacked the data and collaboration technology needed to centrally manage operations of both the supplier and the retailer.

The COVID-19 crisis has shoved into the spotlight the traditional paper-and-time intensive activities associated with Supply chain. Digital collaboration is the need of the hour as retailers explore the possibilities of collaboration across every aspect of the supply chain process.

 

Lack of Visibility in Supplier Operations

Sharing of information across the supply chain is key to avoiding potential demand-supply issues. Grocery retailers in particular, during the COVID-19 crisis need visibility across the supply chain to better address issues like OOS (Out Of Stock) and surplus stock of non-essentials.

Information needs to be shared with all supply chain stakeholders for logistic decisions to be made that help businesses to operate more efficiently. Yet, according to Supply Chain Digital visibility is a central challenge for supply chain managers today, with 94% of companies admitting that they don’t have full visibility into their supply chains.

To mitigate these issues in the short-term, supply chain leaders are working to create transparency and rapid response capabilities. One of the ways to do this is to use a technology platform that brings suppliers and manufacturers together for visible collaboration.

 

Volatile Inventory Demand

During this crisis situation (or any crisis situation for that matter) it is not unusual for consumers to panic hoard essential commodities. This results in a stress on retailers like grocers and pharmaceutical companies to manage an unexpected spike in product demand.

A Nielsen data report indicates that sales of oat milk, surgical masks, first-aid kits and other non-perishables spiked late in February 2020 in response to coronavirus fears.

On the flip side, non-essential items pile up, as there are no takers. Retailers today are struggling to know their current inventory supply, and be able to replenish demand essentials without sustaining losses.

Many retailers are managing this by ramping up warehouse and distribution numbers, while others are using warehouse management technology to assess inventory, predict peaks and coordinate employee shifts to keep supply moving. Retailers are also being pushed into moving inventory and resources to new channels. Because of today’s social distancing norms, there’s been a growth in ecommerce orders, and retailers are moving inventory by making it available online for purchase and working with distribution channels for fulfilment.

RIS News reports that Amazon Fresh and Whole Foods Market have increased order capacity by more than 60% due to COVID-19. The number of Whole Foods Market grocery pickup sites has grown to over 150 in the past few weeks, up from around 80 stores. Additionally, Amazon's store in Woodland Hills, is now serving as a temporary online-only store that's focused exclusively on fulfilling grocery delivery orders.

 

Limited Supplier Dependency

Pharmaceutical companies in particular are currently facing a crisis in their supply chain, as a majority of active pharmaceutical ingredients are developed In India and China. 

According to Thomas Derry, CEO of ISM, “Organizations who diversified their supplier base after experiencing tariff impacts, are potentially better equipped to address the effects of COVID-19 on their supply chains.”

While some pharmaceuticals often have a redundancy in drug supply of such drugs, companies which contract with multiple suppliers can prevent disruptions from causing shortages.

 

Lack of Data for Agility

Any technology platform that can help retailers stay on top of their supply chain activities, relies heavily on standardised data to collaborate and communicate effectively. However, for most retailers, data is still siloed and not standardised for sharing on collaborative platforms. 

Yet the use of information technology to share data between supply chain partners is crucial for agility. For retailers to be able to survive amidst chaotic demands, information sharing between and within the supply chain players is a critical requirement towards optimizing supplier-retail relationships.

 

Where Will Retailers Go From Here?

Shifting from a traditional supply chain to an end-to-end information management, can help retailers respond faster, reduce redundancy and maintain supply chain efficiency.

For more information on how your retail business can manage its supply chain during this crisis, Learn more on " Minimising Supply Chain Disruptions During COVID-19"

And another year of NRF Retail BIG Show is over! 

If you read our previous round-up then you’ll know some of the top retail influencers had high expectations.

Did they find what they were looking for? 

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Personalized experiences are always blissful. Be it a personalized workout routine at the gym or a spa treatment, it always feels like a luxury. Personalization today is not just in terms of including a prospect’s first name in an email directed to them. It is the next step in the era of Hyper-personalization.

In the third session of ‘Perspectives’, a Linkedin live series from Manthan, Raj Badrinath, Vice President, Marketing & Ecosystems and Michael Ni CMO Sales & Marketing of RichRelevance spoke about hyper-personalization as the next frontier, customer experience, and the whole science behind it. Read on to get expert perspectives on personalization, and what scenarios in which retailers and brands are deploying this technology.

Raj: Let me begin with this Michael, what is all the hype around ‘hyper-personalization’? Tell us a little bit about it.

Michael Ni (Mike): So the thing about Hyper-personalization is that we all inherently know about it. When you walk into your general store, for instance, imagine the shopkeeper has already laid aside special meat he just received and he tells you the story behind the meat while educating you about it. By doing so, the shopkeeper has not only made it easier for you but also given you a meaningful experience and helped you learn. This is the perfect example of hyper-personalization.

Raj: We know that the entirety of the Marketing approach has been around Segmentation for the longest time. Would you say it is the same as the personalization or hyper-personalization approach?

Mike: No, Segmentation is not Hyper-personalization. Today, Marketers are still stuck in the old ways of thinking, even though they have more technology to go beyond segmentation. Yes, Segmentation involves AI-driven approaches but is still not about the individual, what they want, what they care about or their intent at that point in time.

Raj: Now that we understand segmentation is definitely not the same as hyper-personalization. What nuances should a marketer look into to understand this difference?

Mike: Frankly, Marketers will have to be at a certain level of planning and abstraction since they need to be thinking about the persona, the content, the journey that the customer is on. Let me give you an example of this. Let’s say I have been investigating all over the internet and stores about quality shirts. So when I actually walk into the store, I am as a customer, far along enough on my journey and do not necessarily need to be educated about it. I just need to buy. A deeper understanding of this journey of a customer is what will help the marketer create a better experience.

Raj: That makes so much sense. So tell me about the consumer’s point of view here. As a consumer, is there any end-state that I can determine in any way?

Mike: Looking back at the example of the shopkeeper that we were discussing earlier in this conversation. The experience was well beyond just buying something from a store. As a customer, since the experience was memorable, the next time that I think of buying something, at the top of my mind will be that shopkeeper and the experience of buying that product.

To understand the kind of experience and relationship brands are vying to build with their customers, let me give you an example. Imagine you walk into a grocery store and you are given a cart with a screen that lists items for you. So as you move ahead, you pick what you want and tick things off your list. Based on what you pick, the system uses the information to build a profile and personalizes the experience for you. When you leave the store you get a reminder of the things you may have missed. This is the kind of customer interaction that brands are increasingly trying to develop with their customers.

Raj: All of this hinges on data. What happens in the case of customers who visit the website for the first time and we don’t know anything about them?

Mike: It’s a perfect question. When a person visits your website even if it is the first time there is a tremendous amount of information available already including where they came from and what device they are using. Take a restaurant for example that does not necessarily know all its customers. With the first couple of orders placed the restaurant tries to recognize who the individual is and builds a profile. Similarly, with every click or choice, a customer makes online helps build a profile right from the first visit to the website. That is how a customer moves from being someone who is completely anonymous to someone who is showing behavior hence giving you the opportunity to personalize.

Raj: Let’s talk about the AI now. Netflix, for example, is considered one of the masters of hyper-personalization. What aspects of it are common and deployable in other customer industries?

Mike: Let’s take Netflix first. I think it is important to talk about the marketing approach and also the technology you use with the algorithm. Netflix uses personalization extensively and uses every opportunity to present its customers with the right content. It lets customers consume content in the way they prefer instead of bombarding them with a hundred irrelevant options. Another example is Google which uses an Ensemble-based approach. This approach uses multiple learning algorithms to get better predictive performance. It is important for any business to understand which algorithm is working where in what part of its jo Hyper-personalization is a technology that makes it easier to do things that are otherwise manually not even practical. This technique allows you to focus on the intricate details of your customers that are not available while us Experience. This solution combines a Customer Data Platform, Retail Marketing, and Merchandising solution, and Real-time Personalization powered by advanced data science and algorithms. ing traditional personalization of their data. It really is the next big step in marketing!

Manthan recently announced a strategic alliance with RichRelevance, a market-leading personalization platform to deliver an end-to-end Algorithmic Customer

It’s that time of year again!

Retailers around the world are preparing for the NRF Retail Big Show 2020, and once again Manthan speaks to several retail influencers to find out what they are excited about seeing.

This year, Manthan will be talking about Algorithmic Customer Experience at Booth #5747 .

But you’ll love to know that our friends and retail experts are looking forward to everything from sustainability to the snacks being served in the press room!

MANTHAN ASKED: “What big retail idea do you hope to see at NRF RETAIL’S BIG SHOW 2020?”

 

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From futuristic technology to the latest visionary business cases, NRF 2020 brings together a platform for the industry to showcase what could be. To get a sneak peek of how you could offer your customers an enhanced retail experience through algorithmic programming, visit www.manthan.com/nrf

We hope to see you there!

   

According to reports, orders placed via smartphones and mobile apps will become a $38 billion industry and makeup nearly 11% of all quick-service restaurant sales by 2020. In 2016, a Nielsen study showed us that millennials are the largest group of smartphone users, as well as the generation that dines out most frequently. In addition to this, the past few years have seen users of all ages become increasingly comfortable with app-based purchases. In fact, according to research from App Annie, global consumers ordered meals on mobile 130% more in 2018 than in 2016, and worldwide downloads of the top five delivery apps grew 115% during the same period. It’s no surprise then that many restaurant businesses are eager to explore the various ways they can leverage this booming trend to impact their business.   Let’s see some of the ways this can be done:

Activate users in real-time to drive sales

Advanced analytical solutions can help proactive marketing managers automate their marketing campaigns to nudge users who added items to their cart but didn’t transact. By utilizing abandonment marketing techniques in real-time, such as timely in-app support restaurateurs can help improve conversions on mobile apps. Taco Bell’s mobile ordering successes are partially attributed to in-app suggestions to guests to create their desired meals, a tactic which many believe is paramount to combatting mobile shopping cart abandonment.  

Customer microsegment-based promotions

Using the right analytics, marketing teams can micro-segment customers based on time of transactions and order preferences. This gives the campaign manager pinpoint control over promotional messages to any segment resulting in improved conversions. For example, health-conscious users can be targeted with low-calorie multi-grain pizzas during their app sessions.  

Location-based targeting to drive customers

App-driven location data can be used to trigger push notifications to customers based on their city locations along with information on their last purchased items or favorite combos. Innovative restaurants can leverage location-based targeting creatively to acquire new customers. One such campaign run by Burger King targeted customers within 600-feet of a McDonald’s to unlock a Whopper for 1 cent through its app in December 2018!  

Up-sell campaigns to maximize customer value

Cross-selling and upselling can help maximize mobile app purchases, by acting on customer purchase data and responding at the most opportune time. Advanced analytics coupled with marketing automation can provide marketing teams with the ability to deliver rich mobile notifications for upgrades, and add-ons based on customer preferences prior to check-out. Starbucks entices customers using the app to try out new offerings or upsize their order, with a scrollable news feed that highlights drinks and food with eye-catching images.  

Time and event-based personalization

By knowing the customers’ preferred time of dining, offering push notifications with deep links can help drive purchases. Advanced analytics can help leverage this customer insight to understand peak times and customer drivers, into to drive sales with timely messages.  

The Mobile Restaurant Future

According to DMI research, the mobile activities most desired by diners include viewing menus, finding the closest locations and placing orders. Restaurants which have the right tools in place can, therefore, leverage the power of mobile technology to increase conversions, build loyalty and improve their market share.

Restaurant owners are sitting on a ton of data – from employee information to mobile apps, supply chain logistics to touchscreen kiosks, e-commerce numbers to social media reviews. BCG reports that four out of five restaurant brands can access a wealth of data from multiple sources, however, only one in five is using that data comprehensively.

If you’re in the restaurant business, you’ve probably already heard a lot about how restaurant analytics can help bring in more customers. But are you aware of the operational, and predictive ways in which analytics can impact other areas of your business?

 

1. Sales: With advanced restaurant business analytics software you can uncover key insights on the performance of stores and products, the productivity of resources, and sales category performance – all in real-time. If sales are down during the first part of a Saturday, knowing that dip can help you send out offers to improve the day’s performance immediately – as opposed to seeing the report on Monday afternoon when it’s too late.
2. Operations: A direct impact on your business is the operational efficiency. Use data analytics for restaurant to see how you’re doing on key operational metrics such as delivery time, cook time, wait time, store efficiencies, labor, and more. Know the performance of franchise owners by region and/or store.
3. Menu: You may already know which menu items are selling the best or doing the worst. But advanced restaurant software can also give you insights into deeper questions such as which products sell well together, what are the top customer choices by demography, how historical sales patterns will impact transaction value and much more.
4. Location: Can data analytics for restaurant help you find the best place to open a new store? Yes, it can! Analyze the potential of a new store location, using location and guest demographics to postulate footfalls and potential sales. Compare and choose the best site for your restaurant with comprehensive data sets that translate into high demand.
5. Mobile App: Improve engagement on your mobile app through in-depth analytical understanding. Know when, where, and how customers use your app in order to engage them with contextual messages in real-time. Encourage mobile app orders based on location, current order, cart components and the guests’ historical relationship with your brand.
6. Customer Satisfaction: Advanced restaurant analytics software should be able to give a view of customer satisfaction by channel and store, allowing deep dive analysis of how Net Promoters Score (NPS) impacts store performance. Using analytics, you can, therefore, identify both broad (across-store) and narrow (within a store) reasons for dissatisfaction down to each guest level.
7. E-Commerce: Analytics enables a finer understanding of online customer purchase behavior, a source of traffic, traffic conversion, preferred offers, typical order size and more. Using this information, you can then influence customers as they place orders by recommending relevant products they might like and minimizing abandonment with timely intervention.
8. Marketing: Restaurant Software enables clarity into campaign performance and its impact on sales. By harnessing customer data from various source systems, you’ll be able to understand your campaign performance from the guests’ context, and deliver personalized 1-1 campaigns on channels they prefer: during the best daypart, on a day they are likely to respond; all using automated marketing.
9. Personalizing: Your frequent guests and your at-risk customers are those with the biggest impact on your bottom line. Analytical behavioral clustering, propensity models and churn prediction algorithms can help you uncover customer opportunities and risks. You can dynamically segment customers on multiple dimensions such as day-part, order value, visit frequency, price sensitivity, taste, occasion preferences and more. By knowing the micro-segment each customer belongs to, you can tailor your messages with specific promotions, reduce churn and give loyal customers more reasons to return.
10. Compliance: Maintaining brand, safety, and employee training standards across equity and franchise stores is critical. Advanced analytics can help ensure operations and food safety compliance, monitor status of employee training, identify talent and understand the impact of employee performance on store performance.

   

Go Beyond Reporting

The sophistication of analytics has now evolved beyond mere day-to day-reports. By bringing together disparate systems, and applying the right advanced analytics solution you’ll be able to uncover the hidden meaning behind all that data. A savvy restaurant entrepreneur can leverage these analytics to make better decisions regarding operations, campaigns, customers, and strategy, to outthink the competition.

We’re here at NRF 2019! And Manthan has taken the time to catch up with other NRF and retail experts. We spoke with Randy Crimmins, EVP/Chief Strategy Officer at Relationship (formerly GoThink!) to understand his expectations in omnichannel marketing, retail technology innovations and the AI-driven future of retail grocery store chains.

MANTHAN: What innovation are you most looking forward to seeing at NRF 2019?

RANDY: For me, it’s all about the connected shopper. I’m interested to see what tangible progress companies are making in terms of creating a truly connected, personalized retail customer experience without and within the store.

What advancements are being made to help retailers 1) truly understand their customers holistically and 2) leverage that understanding to relevantly and personally engage with each of them throughout the shopper journey, online and instore?

MANTHAN: What does the ‘store of the future’ or ‘the intelligent store’ mean to you?

RANDY: I go back to the connected shopper. The intelligent store furthers the connected experience bridging the shopper journey and digital engagement from outside to inside the store.

For example, I receive a welcome message via push notification when I walk in the store that alerts me to personalized marketing deals available for that visit. These offers are automatically added to my digital shopping list and highlighted on my digital aisle map in my mobile app so I can easily locate them. When I check out, my account is recognized as being a top customer, which automatically notifies the front end or store manager on her app, who casually stops by to personally thank me for shopping and make sure I found everything I was looking for that day.

The connected shopper experience leverages integrated retailer systems, customer data, the utility of the mobile app, location services and omni-channel engagement—essentially leveraging high-tech for high touch inside the store. That’s the future and it’s here now.

MANTHAN: What would you say are the top three things grocery retailers need to focus on in 2019, to compete profitably?

RANDY: 1. Infrastructure 2. Infrastructure 3. Infrastructure. Focus on creating the right infrastructure, integration, and processes needed to create highly personalized, relevant connections with your customers online and in-store. Too many retailers are reaching first for the bright shiny objects, without fully understanding the infrastructure needed, or the vision and planning required to deliver the kind of connected customer experience that shoppers are going to demand. Retailers end up with disparate systems and cobbled together processes that don’t integrate, communicate or scale.

Walk around NRF… incredible applications, technology, and solutions everywhere screaming their features. As a retailer, you have to step back, define your vision, create a plan and focus on creating the right data, digital infrastructure and enabling technologies necessary to serve you and your customer’s long term. Digital investment is not a marketing line item—it is as important of an investment as those routinely made for software and hardware in other areas of your business. Change the mindset.

MANTHAN: What are the top omnichannel marketing challenges that retail grocery store chains are still trying to overcome?

RANDY: Retailers are challenged to create connected customer experiences that leverage all channels, and more importantly each shopper’s “channel of choice.” Retailers are also challenged by data integrity and a singular understanding of a customer — “one version of the truth”. Customer account data and integrity is a fundamental and critical component to successful omnichannel engagement.

On the back-side retailers struggle with understanding performance attribution. What/why/how do customers respond to offers, engage with the retailer online and in-store—what device, which campaign, promotion and offer, and taking it further, what was the associated ROI, or incremental gain at a customer level. These are mission critical aspects of being an effective omnichannel marketer, yet the majority of retailers don’t have a clear or complete picture of their efforts or results.

MANTHAN: What recent technological innovation have you seen significantly impact retail marketing?

RANDY: Big Data and machine learning have disruptive potential in retail marketing. Take for example the process that every grocer does of creating the weekly flyer. The majority of supermarket chains today probably still build their ad based on spreadsheets and historical patterns, just like they have for the past 30 years. It is an incredibly labor-intensive process, probably occupying 30-40% of the merchandising and advertising teams’ time each week. Big Data and AI could transform this process to streamline the workflow, as well as recommend the items that should go into the flyer based on localized customer data, historical purchase behavior, seasonality, trending, inventory levels, even weather-related data. There’s no reason why using AI a retailer could not automatically build the weekly flyer without any manual intervention.

You can also take this “intelligent” flyer concept further online, by taking all the advertised items for that week and presenting them to each shopper in a personally curated form. A truly personalized marketing solutions for every customer, every week.

We are doing this today and seeing significant gains in terms of engagement, incremental activity, and ROI. You roll it all up and the total efficiency and effectiveness gain potential are huge, and that’s just one marketing vehicle.

MANTHAN: AI promises to make data-driven processes more intelligent. Which retail segment do you foresee experiencing the biggest impact?

RANDY: AI and Big Data are beginning to transform retail marketing. Of all the retail verticals, grocery has typically been a laggard from a data sophistication and technology standpoint. The irony is that supermarkets typically have the most data and transactional volume, pioneered the capture of individual data via loyalty programs, and yet they lag other industries in their ability to leverage all this customer information for the betterment of their business.

If any industry is poised to reap the benefits of AI for marketing, it has got to be grocery. There is so much upside. The one example above with the weekly flyer could be connected to the inventory system for automatic ordering/replenishment.

In fact, we are seeing AI being used by forward thinking companies like Manthan to manage inventory, minimize shrink, optimize assortment and promotional performance. Disruption is coming to grocery and it will be led by big data and AI.

MANTHAN: Thank you, Randy!

Big Data Analytics & Data Scientist. Global Speaker. Astrophysicist. Space Scientist. And in addition to all those hats, Dr. Kirk Borne is the Principal Data Scientist and Executive Advisor at Booz Allen Hamilton, and a globally acknowledged influencer since 2013. This week Manthan talked to Kirk to delve into his thoughts on big data analytics solutions for data driven discovery and decision support, and innovating using data science.

MANTHAN: Your personal journey in the field of big data analytics is an exciting one to read . What is the biggest surprise you’ve experienced in this rapidly growing, data driven world? 

KIRK: The biggest surprise that I have experienced is how incredibly rapidly the world has woken up to and adopted the power of data and the power of algorithms. I worked in this field for many years and it was hard to get anyone to take it seriously 10-15 years ago. But in the past 5 years, the field has exploded, including startups, new businesses, new lines of business in old organizations, data science advocates in all types of organizations, the number of use cases across all sectors, and the demand for data scientists and data scientist training programs.

The growth of interest, applications, tools, startups, and people working in this field almost seems to be *faster* than exponential.

MANTHAN: You’ve shared an example in our round-up on the impact big dataanalytics has made on society. Could you give us an example of how analysis of big data has helped improve a business situation?

KIRK: A very large financial services company (we’ll call it ABC) was concerned about customer attrition. Whenever a customer took their investments to another business, ABC lost money. So, ABC decided to explore their customer engagement data to see if they could find a precursor signal in the data that indicated when a customer was perhaps likely to take their investments out and move their funds to another business.

ABC invested approximately one million dollars in a “proof of concept” project to search the data and build a model of customer attrition. They did find a signal in the data, which was simply the sudden increase in the frequency of customer logins to their online account in the month prior to withdrawing their investments. So, ABC deployed a friendly customer engagement program in which they reached out to those customers whose monthly login frequency suddenly increased — ABC sent information about a new online investment calculator, investment performance metrics, new investment strategies, updated FAQs, financial management advice, tools to simplify reinvesting in their other financial service products, etc. At the end of the 3-month “proof of concept” test period, ABC estimated that their one million dollar data science investment had saved the company one billion dollars in customer value!

That was an ROI of $1000 for every $1 investment in their program. So, the company decided to invest in a much larger permanent data science team for greater customer engagement and marketing insights.

MANTHAN: As the Principal Data Scientist at Booz Allen Hamilton, how do you feel perceptions have changed (for good or bad) towards big data analytics solutions?

KIRK: I believe that the worst of the “big data” hype is now behind us. A lot of growth in the data science and big data analytics fields has already taken place in the past few years, despite all of the negative hype. Now, with the hype being diminished, we are settling down to greater growth, investment, innovation, and value creation in the field. So, the perceptions are definitely changed for the good!

MANTHAN: What recent problem have you helped solve by applying a data driven scientific solution?

KIRK: I cannot discuss client-specific problems and solutions, but one case that we are developing for a future potential client is around a fairly well known and common problem in the field of talent analytics: using data and modeling techniques to predict employee performance, job satisfaction, and possible attrition.

We considered an ensemble of different predictive modeling techniques that gave greater insights into the problem than a single model approach, with most of our focus is on the employee attrition problem (which is much like the customer attrition problem mentioned above): what are the key signals in the data that might indicate when such an outcome is likely to occur?

MANTHAN: What do you imagine the future will be like when we have greater computing capabilities to fully harness the potential of our big data?

KIRK: There are 3 essential contributors to big data analytics solutions and data science success, and why big data science is so popular these days, are these:

• larger and more comprehensive data sets.
• more efficient and effective algorithms.
• faster more powerful computing capabilities.

As computing capabilities increase, then similarly will our abilities increase to explore even greater dimensions and combinations of dimensions of much larger data sets.

The insights to be gained will continue to grow in proportion to the computing power that we can apply to the problem. The combinatorial explosion of different combinations of diverse data sets to be explored will become even more enormous as the Internet of Things grows in diversity and ubiquity. The discovery potential from all of these new acquired data will be lost unless we also acquire greater computing capabilities.

So, I expect that the 3 essential contributors to big data science success will continue for a long time to come!

MANTHAN: Thank you, Kirk!

In anticipation of NRF 2019 next week, Manthan caught up with the retail experts from Mindtree; Vinaysheel Palat Global Head of Consulting for Retail, CPG and Manufacturing and Ronojoy Guha, a specialist in predictive analytics platform for Merchandising, Stores and Supply Chain logistics; to talk about technology, predictive analytics platform and the future of retail.

MANTHAN: What does the ‘store of future’ or ‘intelligent store’ mean to you?

VIN & RONO: Future stores would become experience centers rather than just market places, a destination providing multiple services to customers, like dining, dry cleaning, and shipping. A one-stop shop for all needs.

The store sizes are likely to shrink as they look to bring in granular clustering based on the demography of the location. E.g., currently grocery stores use much space on bulk goods, these would be shrunk and taken to the backroom and fulfilled on orders. While their backroom stores would become distribution centers for their online orders, bringing in true omni channel, not just from a consumer standpoint, but from a supply-chain as well.

Technology play will be much higher, there would be more cashless and card-less transactions, curb-side pickup, etc. We will see more differentiation in store formats catering to local demography. Customer segmentation would be used to tweak experience.

Grocery store experience centers would be different compared from downtown to suburbs. The store itself would have a personality and how it will have a conversation with its shoppers would differ. E.g., Suburbs with young families would perhaps have centers where recipes with organic food are cooked. A fast-moving store in downtown would focus on information.

MANTHAN: What would you say are the top three things retail stores need to focus on in 2019, to compete profitably?

VIN & RONO: The most significant would be personalization at an individual consumer level. Consumer behavior would have to be analyzed to offer differential pricing, personalized and real-time promotions, and better service. Personalization would not be restricted to consumer but would extend to the store and products as well. Depending on the store format and the products being offered, retailers would look at dynamic assortment, driven through an app in the store.

Pricing is a relatively ignored area in retail today and has huge potential to increase profitability for the store.

The other areas would be traditional levers of Cost and Risk management. Labor is the biggest operating cost component for a store (25-30%), can technology reduce this? How can inventory and shrinkage be reduced? Retailers will have to think about these questions. E.g., retailers spend significant money each year servicing claims from customers who meet with minor accidents in stores, how can these be avoided or reduced. Energy consumption within the store is another cost driver that would be rationalized.

Retailers must also revamp their processes to embrace omni channel in its true sense, be it making replenishments in smaller batches in a day, better managing staff with rotation of shifts, and such, to make their store future ready and have a meaningful conversation with their customers.

MANTHAN: The phrase ‘Data is the new oil’ has been popular for the past few years. Have retailers realized this value? What is stopping them from maximizing the value of data?

VIN & RONO:  Like oil, data is invaluable, not just for retail, but any industry of today. It is going to revamp the retail sector in coming years and stop the physical store from extinction and becoming the dinosaurs of our generation.

But just like oil, data can be inflammable too, if not utilized effectively. We see data to be regulated increasingly in the future, it has already started in EU with introduction of GDPR. But in future, data would be marketed, sold, and utilized in pre-set conditions.

Retailers will have to be judicious on how they collect and use data. How the data is analyzed and benefitted from would be most important, rather than racing to collect more and more of it. Governance standards would have to be established with how data is standardized. Many companies today are not doing a good job of this.

MANTHAN: Can you share your thoughts on predictive analytics and it’s expected impact on retailers?

VIN & RONO: Predictive customer analytics has had a giant evolution in a very short time and it now is a necessity, a given. Retailers need to utilize this in physical stories to maximize the potential. It should be used for defining pricing, inventory, merchandising, and even number of stores needed.

Predictive customer analytics in future should be used beyond this, it should help influence consumer behavior. So influence external entities rather than just internal. Consumers should become influencers of your brand.

The retail sector today is highly under-leveraged in this area. It has tremendous un-utilized opportunity to gain from predictive analytics. Retailers should invest in this in 2019.

Retailers need to take the organization along to make any predictive customer analytics program successful. Technology is one aspect, but business should understand the value and be an equal partner.

MANTHAN: AI promises to make data-driven business processes more intelligent. How do you see this impacting retailers?

VIN & RONO: AI has infinite potential to disrupt retail. This should be looked at in two broad spectrums.

At the customer facing end, we have seen apps from home improvement retailers where you can take a picture of your room and the app shows you assortment of products enabled through deep learning. Or take a picture of a pair of shoes and suggestions roll up on your screen based on your preferences.

On the backend, AI can impact on how pricing algorithms are defined to make almost real-time price suggestions for individual customers. It can help take decisions on inventory movement, or control energy consumption in the stores, or guide store associates.

MANTHAN: What innovation are you looking forward to seeing at NRF 2019?

RONO: I am looking forward to seeing how AI or Robotics would impact the store of the future.

VIN: I am really interested in learning how this high influx of technical innovations that are replacing store associates (think Amazon Go) replace the human touch, empathy, or need for dialogue that a shopper visiting a physical store looks for.

Thank you Vin & Rono!