THE PRESENT AND FUTURE OF RESTAURANT ... - Personica

THE PRESENT ANDFUTURE OFRESTAURANTPERSONALIZATION

BACKGROUND:INDUSTRYPARTICIPANTS Over the past 15 months, the restaurant

industry has undergone a massivetransformation. Restaurants of all sizes,types, and geographies have addeddigital modes of ordering, delivery, andcommunication to their existing on-premise tools. Other industries havegone through similar transformationsover the course of many years. For therestaurant industry, the pace of thisadoption was unprecedented.

Digital technologies inevitably bring agreater focus on personalization andon the large scale collection andapplication of data to improvecustomer satisfaction and to optimizethe results of financial and marketingdecisions.

Recognizing that restaurant executivescould learn a lot from other industrieswhen it comes to personalization,Personica hosted a series ofroundtables throughout the first half of2021 to foster joint learning. Thesesessions included keynotepresentations from leaders in thehospitality, media, and advertisingindustries who have alreadyimplemented successfulpersonalization programs. After thekeynotes, participants discussed thepossibilities for applyingpersonalization, approaches forbeginning their journey, potentialchallenges, and conceptualframeworks for capturing and applyingdata. Ultimately, the group ofparticipants synthesized their findingsinto a set of frameworks that therestaurant industry can use to expediteits path to personalization.

At the conclusion of these roundtables,Personica assisted in consolidatingand articulating the informationcovered. This paper outlines keylearnings and implications from thesediscussions, developed by andapproved by this group of contributors.We are excited to share theselearnings, in the hope that it helps ourindustry continue evolving, improving,and thrilling guests.

Presenters and discussion leaders:Justin Basilico - Director, Machine Learning and RecommenderSystems, NetflixKristen Hayashi - Sales Strategy Director, Ad Innovation,PandoraMatt Ryan - Former CMO, StarbucksRishad Tobaccowala - Author, Restoring the Soul of Business:Staying Human in the Age of Data; former Chief Growth Officer,Publicis GroupeChris Miller - Former VP of Marketing, Taco Bell, Raising Cane’sChicken Fingers, Smoothie King, Bagel Brands

Thought Leaders:Chris Ruszkowski VP, Marketing, Bad Ass Coffee of HawaiiHannah Hoyt Head of Demand Generation, BBotTrevor Fullwood Technical Product Manager, BBotLiz Bunker SVP Marketing, Veggie GrillCarrie DeMallie Sr Marketing Manager, Black Bear DinerCheril Hendry CEO, brandtailersMichael Schatzberg Managing Director, Branded Strategic HospitalityMike Lukianoff CEO, ChamberlainGeorge Gee Consultant - Marketing, Loyalty, CRM, & Strategy,Chipotle EuropeMike Simon Board of Directors, CKE RestaurantsJohn Pinkard Marketing Lead, Platform Services Division, Coca-ColaGaurav Pal PhD, CornellDan Bejmuk CEO, DreamBox CreationsMichael Kilwein Director of Marketing, Earl EnterprisesChristine Lorusso Director of Digital Marketing, FirebirdsJason Carrigan VP, Digital Marketing, Focus BrandsDan Gertsacov Chief Commercial Officer, Focus BrandsHeather McKeon CMO, GringosAmy Jo Owens Director of Marketing, GringosTom Cook Co-Principal, King-CaseyCynthia Coffield Director of Omni-Channel Marketing, Landry'sWill Robinson CMO, Ledo PizzaJen Bell CMO, Lettuce Entertain YouBrooke Fitz CRM & Loyalty Analyst, Little CaesarsKami Timko Director of CRM & Loyalty Analysis, Little CaesarsShalini Rajhans Director of Marketing, Little Caesars of CanadaJoan Hansen Director of Marketing, Lucille'sMayank Patel Global Director of CRM, Loyalty, & Personalization,McDonald's Corp (prev)Ahsan Jiva Director of Digital Strategy, Mellow MushroomAndrea Von Utter VP, Marketing, Miller's Ale HouseAndrew Hagan VP, Guest Engagement Marketing, NoodlesNica Ysay Digital Marketing Brand Manager, Pieology PizzeriaMike Burns COO, RaverDarden Coors CEO, The Salad CollectiveMelanie Benitez Assistant Brand Manager, TOGO'sJim Ilaria Former CEO, Too JaysCarolyn Hosna VP, Marketing, White Lodging

EXECUTIVE SUMMARY

Personalization is a requirement and an opportunity for restaurants

Consumers increasinglyexpect personalizationAs restaurants continue to adapt to a hybridonline and on-premise service model, they’ll seean uptick in customer demand for consistenttailored experiences across each touchpoint. ITand marketing teams are investing in technologythat helps them break down their guest data intohigh-converting campaigns and connect withtheir guests across multiple touchpoints. In anincreasingly digital world, data-basedpersonalization is both more possible and morecrucial for building customer loyalty throughexperiences.

There's a huge opportunity here for restaurantsready to take it. In a recent Personica case study¹,one national brand saw an increase from 4.56XROI to 59.3X ROI simply by personalizing the typeof burger featured in their annual promotionbased on the guests’ past purchase history.

There’s also risk in taking a “wait and see”approach. According to a recent report fromTwilio,² 45% of consumers say they’ll take theirbusiness elsewhere if brands fail to offer apersonalized experience. If personalization isn’tthere or only exists on-premise, guests may buildloyalty with brands that offer custom-tailoredexperiences across all touchpoints. Restaurantguest loyalty will be won and lost based onquality and consistency in customer experiences.

The hospitality industry is no stranger to theconcept of personalization, whether it involves thebartender who knows his/her guest’s favoritedrinks or Danny Meyer’s influential book “Setting theTable.” Even global QSR chains have local staffwho get to know their regular customers or whoput customer names on their coffee containers.During the course of our roundtables, it becameclear that stakes are higher than ever.

Other industries with a longer history of digitalservices have set a precedent. Netflix andPandora stand out in this space, and highlightboth the building blocks and challenges ofundertaking such an initiative.

Some restaurant brands are already advanced inthis type of customization; Starbucks and Paneraare leaders. The decade-old Starbucks Rewardsprogram gathers a huge amount of data oncustomer spending and preferences, leveraging itto personalize the experience for each guestbased on their unique preferences and spendinghabits. As of October 2020, the StarbucksRewards Program had grown to more than 19.3million members, generating nearly 50% of thecompany’s total revenue.³ Similarly, according toformer Panera CMO Mike Simon, a significantpercent of the brand’s transactions come fromloyalty program members, providing the digitaldata to personalize experiences at each level.

The restaurant industry canlearn from personalizationpioneers

This group developed a 5-step process forgetting started. By learning from success storiesand keeping a few key principals in mind,restaurants of any size can apply thispersonalization roadmap to their marketing andguest communications.

Participants identified a keyset of barriers and enablersunique to the restaurantindustry.

DataAn explosion of data from new digital purchase channels willenable personalization at scale for restaurant guests. Acustomer data platform that provides a 360 degree customerview helps brands determine who to target with various offersand campaigns.

Decisions

Dialogue

By using advanced analytics to develop decision logic andalgorithms, restaurants can break down guest profiles todecide what offers, prices, and engagements to serve to eachcustomer.

Dialogue addresses the how of personalization - deliveringmarketing and experiences across channels, then feeding thatresponse data back into the customer data platform.

Building a fully personalized platform using existing data andsystems should start with five areas of communication withcustomers: Loyalty Programs and Offers, MarketingCommunications, Menu Presentation and Pricing, OrderInteraction, and Team Member Communications

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The Personica roundtablepractitioners developed a 3D model for applyingpersonalization:

Personalization is now a necessity forrestaurants, and it looks different post-pandemic

Consumers expect and reward personalization Numerous research studies indicate thatconsumers expect and reward personalizationand that brands are delivering at a slower ratethan desired. According to a study conducted bytechnology firm Twilio², 69% of consumers say theyappreciate personalization, as long as it is basedon data that they’ve shared with a company. Infact, 60% of the people surveyed indicated thatthey were likely to become a repeat buyer after apersonalized experience, up from 44% in 2017.

A similar study by BCG⁴ clearly indicates theimpact of personalization on the retail industry.Consumers categorized their experience basedon“high” vs. “low” levels of personalization. Highlypersonalized experiences were found to improveevery part of the sales funnel, including 110%increases in number of items purchased, 40%increases in average order size, and 20% increasesin net promoter scores.

When it comes to restaurants, one participantexpressed their awe in visiting Gramercy Tavern inNew York City, where they rarely dined, and beingasked, “do you want three cherries in yourManhattan again?” Almost every participant hadexamples of personalized experiences that droveloyalty to local establishments, whether becausethe staff knew them or because they couldcustomize their orders.

High-end hotel concierges and five-star serversset the bar for knowing their customers. Both knowtheir most frequent, highest-spending guests’specific preferences and can anticipate theirneeds. Being personally catered to is a pillar ofluxury hospitality, historically available only to

Many participants discussed how loyaltyprograms, personalization, and data collectioncan go wrong when they don’t fit a brand’sexperience. For example, a loyalty program cancheapen a brand’s value or slow downoperational processes, to the point wherecustomers perceive negative value from them. Ordigital menus can put awkward pauses in themidst of group meal occasions.

With this in mind, participants emphasized theimportance of aligning with the brand’s guest andthe value propositions of its concept. For example,a guest may value speed in a drive thru concept,may value a direct connection with a server in afine dining experience, and may value beingrecognized for a birthday at an occasion-centricrestaurant.

This requires a fine understanding of guestmotivations, behaviors, and value propositions inadvance of implementing personalizationstrategies.

Personalization needs to fitwith a brand’s valueproposition

patrons with deep pockets. Now withsophisticated guest databases, even casualrestaurants can personalize customerinteractions, and infrequent, low-spendingcustomers can enjoy experiences customized totheir tastes.

During the pandemic much ofthe world changed their habitsand went digital, creating amassive opportunity

The pandemic is driving a global re-invention. Inthe past 11 months 75% of consumers have tried anew shopping behavior⁵, and most intend tocontinue even after the return to normalcy.

Consumer interactions are steadily shifting toomni-channel experiences. For example, the mostupscale restaurant in Chicago has added a drive-through, and the movie industry is experimentingwith a streaming-first model. There will be nogoing back once customers get used to thesenew access channels, and restaurants will have toexpand to varied guest touchpoints to compete.

The exponential rise of restaurants’ digital offeringsin the last year has had a valuable side effect forbrands aiming for a fully customized guestexperience – a treasure trove of data on individualcustomer behavior. 60% of restaurant users planto continue ordering digitally⁶, and digital ordersare expected to grow to over 50% of total industrysales by 2025⁷.

It’s important to note that digital ordering is notlimited to off-premise dining. While restaurantswill be motivated to use in-store digital orderingto control cost as wages continue to rise, guestsalso appreciate the seamless experience of adigital environment. Tools like kiosks, tablets, andapps bring digital experiences on-premise, andintegration with loyalty programs and CRMcreates a wealth of guest-centric transactiondata. In-store digital ordering will even bring cashbuyers into the data stream with easier, saferordering and links to loyalty program rewards.

Since delivery and pre-order pickup interactionstake place outside of the restaurant, their growthreduces physical limitations like static menuboards or printed menus that can’t be easilychanged. Ghost kitchens and virtual brands arethe ultimate manifestation of this trend. With noconsumer-observable physical location, thesecompanies can maximize the potential of onlineorder data to create personalized menupresentation, ordering, and delivery experiences.

Customers are now gods

As round table presenter Rishad Tabaccowala, Author of Restoring theSoul of Business: Staying Human in the Age of Data, boldly stated,“customers are now gods.” Technology changes enable andencourage shifts in consumer behavior. The computing power in ourpockets, where data talks to data and is facilitated by artificialintelligence, means consumers now have exponentially more optionsfor features and customization. Customers expect marketingmessages to be delivered how they want, when they want.

Because of these shifts, marketers must adjust their approach andexpand their thinking. Brands no longer empower and enableconsumers -- the consumers are already empowered. Restaurantguest experiences now go far beyond traditional on-premise dining;they include online ordering, delivery and pickup, online reservations,social media interactions, and reviews. With more than 90% of guestsresearching online reviews for a restaurant before they visit⁸, each ofthese touchpoints must be optimized and personalized to attract newguests and keep loyal customers coming back.

When all of these experiences are connected by data, personalizationcan reach new levels. Imagine a scenario in which a customer tries anew sandwich special on-premise, then orders online the followingweek. The in-person transaction data can be used to recommendsimilar specials in the online interface, as though the guest is gettingrecommendations from their favorite server.

Learning from experts: Three case studies in personalization

NetflixThe restaurant industry can learn from the success of others, likepersonalization master Netflix. Justin Basilico, Director - MachineLearning and Recommender Systems explained how Netflix buildsrelationships with their members by specifically craftingexperiences to “spark joy.”

Netflix considers each member touchpoint an opportunity to makea recommendation, and extensively customizes how theycommunicate to their members. For example, there are at leastnine different images for the show “Stranger Things” that couldappear on a member’s home page based on past browsing andstreaming history.

Datacollect across timeincluding both implicit(based on what theywatch) and explicit(member-provided)feedback.

Netflix improves theirmembers’ experiences bypersonalizing touchpoints(show recommendations,images, emails) based onfour ingredients:

Metricschoose the bestmeasures ofsatisfaction.

Algorithmsinterpret and act onthe metrics. Basilicocovered severalalgorithmictechniques,highlighting the needto experiment withdifferent approaches.

Systemsbuild systems thatallow for rapidexperimentation.

Netflix started with easier to track metrics such as ratings, then tomore sophisticated metrics. This evolution led to the current level ofpersonalization where virtually every member touchpoint is arecommendation. Basilico emphasized the importance of startingby establishing metrics before developing algorithms, thencontinually testing and improving.

You may have seen one of these “Stranger Things” images basedon your past Netflix behavior

Declared information the customer shares upon sign-up

Pandora further customizes the listener experience using three kinds ofdata:

Observed what the customer listens to and what device they use

Inferred based on listener behavior - for example, people who switch tokids’ music during after-school hours are likely parents

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Pandora

Kristen Hayashi, Pandora’s AdInnovation - Sales Strategy Director,shared how Pandora tailors customerinteraction through messaging. 80%of consumers are more likely to buyfrom a company that personalizestheir content⁹. We are now living in a“culture of me” - almost everything webuy can be customized - and instantgratification is crucial to success,especially for Gen Z.

Pandora personalization also startswith data, via the Music GenomeAlgorithm - a data taxonomy thatscores songs using up to 450attributes. The scores are then usedto suggest new tracks with similarattributes to those the customer liked,and hide songs with similar attributesto those the customer disliked.

Pandora varies listener engagement throughout the day based onobserved and inferred data about the listener’s activities andmoods

Starbucks

Personalized promotions - using the 16 million (US) memberloyalty program, Starbucks sends personalized offers. These mayinclude new product suggestions based on customers’ pastorders, or cold drink features on hot days.New product variations based on detailed customer behavior.Dynamic menus, with revisions based on customer, location, andtime.

Matt Ryan, former Starbucks CMO, gave insights into Starbucks’leadership in applying personalization to restaurants. As one writeraptly said, Starbucks “isn’t a coffee business — it’s a data techcompany,” gathering data from more than 100 million transactionsper week¹⁰.

Starbucks launched its Starbucks Rewards program, driven by itsdigital flywheel strategy, which features:

With suggestions for new food and drink choices, customrecommendations according to time of day, and discounts thatengage customers and keep them coming back, Starbucks hassucceeded in building loyalty driven by personalized marketing.

THE 3D MODEL

A framework for personalization in therestaurant industry: Introducing the 3D model

Data (Customers)

Declared: information the customer shares, such as name, birthdate, location, and ageObserved: behavioral information that can be measured, including visit frequency, transactiondata, purchase history, average check size, and order methodInferred: information that can be guessed based on customer behavior - for example, if acustomer has never ordered a dish with meat in it, they are likely a vegetarian

Every personalized experience begins with strong data. With detailed customer profiles that includetransactions, behaviors, preferences, locations, and demographic data, restaurants can createmessages and offers that drive loyalty and repeat visits. A customer data platform that provides a360 degree customer view helps brands determine who to target with various offers andcampaigns.

As shared previously, there are three types of data that are essential to a core CRM platform:

Restaurants gather data from a variety of touchpoints, including loyalty programs, SMS and emaillist signups, online and on-premise order and transaction data, and guest feedback surveys.

69% of consumers are interested in personalized experiences, as long as they’re based oninformation they’ve shared with the company directly (not purchased customer data)². Loyaltyprograms and other guest acquisition efforts are key to expanding the customer base andincreasing known customer data through defined program constructs.

One challenge restaurants face is linking together customer data gleaned from online and on-premise interactions. A simple but effective solution is leveraging an offers engine to generateunique redeemable codes for each individual guest, so redemptions can be traced back to thecustomer regardless of their order platform.

Storing all customer data in one centralized CRM platform provides greater control, privacy, andmachine learning potential.

Personalization at scale requires orchestration ofthe 3Ds: Data, Decisioning, and Dialogue.Effectively enabling each of the 3Ds drives threekey results: Customers, Content, andCommunications. In a successful 3D personalizedmarketing strategy, Data determines the “who,”Decisioning zeroes in on the “what,” and Dialoguedrives the “how.” Enabling these capabilities foreach of the 3Ds is the key to unlocking the fullpower of personalization.

THE 3D MODEL

THE 3D MODEL

Decisions (Content)After a strong customer data set is collected, the next step is to decide what to do with it. By usingadvanced analytics to develop decision logic and algorithms, restaurants can break down guestprofiles to decide what offers, prices, and engagements to serve to each customer.

Customer ScoringWhen creating a machinelearning-driven decision engine,defining what makes a high-valuecustomer is crucial. Once a brandidentifies its KPIs, these can belinked to customer behavior goalsthat enable customer scoring.These scores can then be used tosegment and target customers,whether with surprise and delightreward for a frequent visitor, or awinback campaign for a lapsedguest.

SegmentationMost programs segment members into targetable groups based on factors like visit frequency andkey items ordered. With more data and AI-driven marketing automation, marketing and loyaltyprograms will evolve from segment-level personalization to 1:1 communication rooted in, andautomatically triggered by, individual transaction data.

The first step in this segmentation process is finding scaleable niches big enough to pursue. Forinstance, when a customer is classified as vegetarian (either by declared or inferred data) andvisits the Panera website, they see the “hidden menu” of vegetarian items that are customizedversions of products on the main menu.

Reporting & MeasurementA decision engine can only learn through rigorous testing. A system that supports A/B/Controltesting, tracking, and measurement is key in determining which recommended actions are mostvaluable. This testing can be applied to any set of variables a brand wants to test, from campaignsubject lines and images to price and menu customizations.

THE 3D MODEL

Dialogue (Communication)After customer data has been collected and analyzed to generate recommended pricing,messaging, delivery time, and delivery channel, those recommendations must be put to use.Dialogue addresses the how of personalization - delivering marketing and experiences acrosschannels, then feeding that response data back into the customer data platform.

Dialogue is centered around five main elements: Loyalty Programs and Offers, MarketingCommunications, Menu Presentation and Pricing, Order Interaction, and Team MemberCommunications.

Loyalty Programs & OffersWhen most restaurants think of personalization, the first thing that comes to mind is personalizedoffers for loyalty program members. This can be as simple as delivering offers for celebratory diningoccasions using birthday and anniversary data, targeting non-delivery members with a freeTuesday night delivery promotion, or serving up a surprise and delight reward to the highestfrequency members.

Deeper digital ordering data will also spur personalized acquisition opportunities. Shared digitalordering applications provide the ability to identify non-customers who order similar items fromother companies. Third-party delivery platforms are currently best positioned to offer this type ofcross-customer marketing, but online ordering and loyalty platforms are poised to deliver the sameto their customers soon. For example, a brand with a loyalty program can serve non-members amessage stating, “you spent $$ with us last year, and would have earned XX points in rewards if youwere a loyalty member.”

Brands that create personalized messages from guest purchasing habits and loyalty/CRM data,with additional data overlay like seasonality, see higher engagement and response rates than thosewho don’t. Personica clients are generating more offer-driven ROI using basic personalization, likevarying the featured image to reflect a frequently ordered item. By gathering more order data onmore customers through POS and online order platform integrations, companies can designincreasingly customized messages and truly personalized loyalty programs.

Marketing CommunicationsNot all customer loyalty is built with a loyalty program or discounts. As more guests go digital andrestaurants solidify the data connections between online and on-premise experiences, advanceslike customer identification by name will become commonplace.

Personalized marketing communications, especially across channels, can increase repeat orders,check average, and loyalty when implemented correctly. Using customer data to personalize theimage or subject line featured in a marketing campaign is a simple but effective way to serveguests messages that apply to their individual preferences.

THE 3D MODEL

Customer response data - open rates, click through rates, etc - can also be used to personalize themarketing channel used to reach out to individual guests. By sending push notifications to heavyapp users, emails to those with high open rates, and sms or social media messages to thoseinteracting on their phones allow restaurants to meet the customers where they are.

It should be stated - a strong content management system and campaign management tool arecrucial to personalized marketing communications and their success. By creating and modifyingdigital content and managing all communication channels in one central place, brands can avoidconfusion and overcommunication that could drive loyal customers away.

Menu Presentation & Pricing

A guest who frequently orders the same lower-priced sandwich and sides could be shown anopportunity to repeat the order with suggested add-ons - such as a discounted cold beverageor ice cream on a hot day.Restaurants can tailor upsells based on an initial order that gives clues to occasion. For example,a guest ordering a whole chicken could see options for sides and drinks, (coleslaw, a gallon oflemonade, etc.) priced based on price sensitivity.Rather than being bound to a bi-annual cadence, price increases could occur at guest-level,tailored to individual price sensitivity and frequency. While some of the above examples are inthe future, brands can start experimenting today. For a great first step, try varying the initial pageof your digital ordering interface by market, based on weather variations and what premiumitems are selling well. Track your results against a control group, and voilà - you’ve dipped yourtoe into the personalization pool.

With digital rapidly becoming the predominant order channel where available, there’s a hugeopportunity for brands to personalize menus throughout the ordering process, based on purchasehistory (including price sensitivity), weather, time of day, etc.

Future menu personalization opportunities may include featuring dynamic menus based oncustomer order history, time of day, and weather. For example, a guest who usually orders dripcoffee but sometimes a latte and an egg sandwich could be shown an egg sandwich and lattecombo on a cold morning. A guest who orders lemonade from time to time could be shown acombo featuring lemonade at lunch on a hot day.

New product variations based on detailed customer behavior data are also possible. A guest whoseorder history includes frequent dairy-free modifications or requests for a gluten-free bun could beautomatically offered pre-modified menu items with those dietary needs in mind.

The order process can also employ dynamic pricing and upsells. These might include:

THE 3D MODEL

THE 3D MODEL

Order InteractionPersonalization will of course vary by brand, and personalized order interactions should focus onleveraging data to make customers’ lives easier. By offering guests the option to quickly reorderfrequently or recently ordered items, brands can make the online ordering process quicker andeasier. Even more impressively, by connecting online order data with on-premise reservation systemand POS notes, servers can ask if a guest would like to try the same or similar item to one theyordered online next time they dine on-premise.

It’s important to consider personalization options across all in-person and online channels, including1st party and 3rd party delivery, drive-through, order through loyalty apps, kiosks, and dine-in with aserver. McDonald’s has personalized the drive-thru experience with menu recommendations thatincreased check size and decreased service times. Regardless of the ordering channel, quick andeasy transactions mean more frequent transactions.

Team Member CommunicationMost guests still anticipate a hybrid model of interaction with restaurants, alternating between on-premise and online interactions depending on their desired experience. This means connecting thecommunication customers get from team members to the communication they receive online iscrucial to a cohesive brand experience across all touchpoints.

By consolidating all guest data, including reservation information, online and on-premise orderhistory, and reviews on one central data platform, brands can empower their team members tooffer personalized communication (greeting guests by name) and recommendations (menusuggestions based on past order history) regardless of order method.

Restaurants have unique barriers andenablers for personalization

Restaurants “get” on-premisepersonalization - it’s part ofthe industry culture (but dataand digital are not)There’s no doubt that restaurants alreadyunderstand what personalization means for theircustomers, especially on-premise. The bartenderwho knows every loyal guest’s face and drink orderand the host who remembers a couple’s favoritecorner booth are both natural experts at providinga tailored experience. But the rise of digitaldemands personalization at scale.

By collecting and leveraging user and transactiondata, restaurants will be able to create omni-channel customization for their guests that rivalthe sophistication of digital-only services likeAmazon and Netflix. Imagine marketingcampaigns that promote content preciselyrelevant to their target guests. Think of the upsellpossibilities if menu items were organized basedon previous orders and preferences, coupled withdynamic pricing, adjustable per guest satisfactionand frequency.

While restaurants excel at in-personpersonalization, they’re just beginning to considerthe same level of experience for their digitalenvironment. With the increase in restaurants’digital ordering and online engagement, it’s clearthe restaurant industry is jumping into thepersonalization race with a unique set ofadvantages and challenges.

However, when taking into account the intangiblepersonalization offerings of a dining experience -atmosphere, packaging, and the “people” element- these possibilities expand. It’s possible theanalog nature of restaurant products are in factan enabler to personalization success.

Restaurants have a potential advantage overservices like Netflix in ease of personalizingproducts. Netflix works with entertainmentprogramming that has long development timesand currently limited individual customizationopportunities. Because restaurants already adaptand change menu items based on guestpreferences (type of whiskey in a cocktail, no nutsin the salad) and seasonality, they are set up totailor product offerings to customers in a digitalspace. They also can launch new products faster-- in as much time as it takes to create a newrecipe and update the menu. There are very fewplaces in the world where you can getcustomization for $5, and with restaurants that’salready possible.

Legacy systems pervade

Restaurants’ offers areinherently analog rather thandigital - we eat themThere is concern that restaurants’ ability topersonalize experiences is limited because thereare finite inputs and outputs - some may say thepossibilities are limited to the menu items onoffer.

Restaurants share the challenge of complexmenus built on legacy point of sale systems, withnever ending SKU lists. These systems werecreated for brick and mortar operations, not e-commerce or omnichannel ordering platforms,meaning there’s extra cost and labor for theteams tackling the shift to digital. These legacysystems can pose some unique challenges whentrying to connect on-premise and digitalenvironments, understand what’s known andunknown about customers across touchpoints,determine how much variety to offer, and howthat variety might differ across order platformslike drive-through vs. in-restaurant kiosks vs.printed menus.

While the challenge of offering truly personalizedexperiences can be daunting, restaurants’ existinginfrastructure makes step-by-step evolution to amore tailored experience possible. Leaders inpersonalization emphasize the need to start small- begin with one data subset or one specific typeof personalized communication (promotionsbased on weather data, for example), and expandfrom there.

While this means teams have less bandwidth toexplore new advances in personalized marketing,it also underscores the importance of usingmachine learning and AI to drive personalizationat scale by creating operational efficiency -rather than just creating more work. By leveragingpartnerships with data analytics and decisionengines, brands can start their personalizationjourney without creating a heavier load for theirmarketing teams.

IT budgets are still small

Marketing teams are nowmuch smaller and mightier

One change the COVID-19 pandemic brought tothe restaurant industry was the thinning andrepurposing of marketing teams. Those whoformerly were dedicated to creating campaignsthat brought guests in the door are now alsoplanning events, helping open new locations, andsometimes even pitching in on the restaurantfloor.

Because restaurants are just beginning theirjourney to personalization and expanding into thedigital space, IT budgets haven’t yet caught up tothe demand for digital systems. As a result, manybrands are looking for data platforms andsystems that don’t require complex integrationsor extensive IT oversight to be successful. Thispresents a challenge when paired with the legacysystems mentioned above -- to collect high-quality, actionable data across multiple systemsand port it into an easy-to-use marketingplatform, increased investment in IT will berequired.

In the meantime, restaurants should focus onusing initial data to shift their communicationfrom “one-to-all” to “one-to-segments.”Attempting to jump directly to 1:1 communicationcan hold back initial personalization efforts. Inshort, the personalization journey is a marathon,not a sprint.

The pandemic forced us toreinvent in ways that havefreed the industry fromconstraintsNew advances in restaurant creation, such asghost kitchens and virtual brands, have anadvantage over traditional on-premise models.By conducting all customer interactions andtransactions online, they avoid the challenge oflinking online and on-premise guest dataaltogether. Although virtual brands and ghost kitchens areable to acquire customer data more quicklythrough their online order and delivery models,they will soon need to focus on customerretention and loyalty to remain competitive.These new tech-centric brands have thepotential to lead the industry in building data-driven personalized marketing platforms.

Your 5-Step Path to PersonalizationBringing personalization at scale to restaurants willbe a long road, starting with small steps. Personicahas worked with personalization round tableparticipates to create a 5-step roadmap to buildingpersonalized customer experiences:

Start with an intentional changemanagement plan. Adoptingpersonalization at scale willnecessitate changes in IT,marketing, operations and othercross-organizational functions.

1

2Personalization requires investment.Pay attention to data architecture,taxonomies, asset tagging, and datahygiene. Invest in a good MarTechstack.This technology is gettingstronger – embrace it. Rent, buy, build.After that, analytics is easy. And makesure your choices support yourbusiness case; your personalizationefforts should support ROI.

3Collect and analyze customerdata rather than relying ontraditional market research. Makedata collection customer-centric.Start with the cleanest guest data,then crawl, walk, run. Addadditional data one set at a time.Establish a “taxonomy task force”to ensure all data is structuredsimilarly.

4Bravely support new learning based onguest data, and discard conventionalwisdom. Rely on your data analyticsteam or partners (hire a good one!)to reframe what you know, then test,measure, adjust, and test again. Trackbehavior, and apply customer-levelprofitability to see where adjustmentsin offers, communications, menu,pricing, and order experience makesense.

5Forget about single-purposecreative assets and reimaginecommunication for the digitalapproach - everything must be acomponent in a “communicationsmachine.” The morestandardization the better, soautomate and simplify.

It’s important to lead with a vision, but crawl,walk, run. Create the business use case and findearly adopters - seeing a small customer groupenthusiastically react to a new program can bea powerful proof of concept. Use those cases tobuild support for programs that continuallyreach more customers. And don’t obsess about1:1 personalization right away. Move from one-to-all to one-to-some segmentation first andbuild from there.

PLAN

INVEST

ANALYZE

TEST & LEARN

AUTOMATE

Personalization is crucial for the future ofrestaurant marketing. Future personalizationsimply brings current customization bestpractices to scale.

Restaurants of all types are already experts in on-premise personalization - it’s part of our DNA asan industry. Think of the coffee shop that prepares a regular patron’s favorite drink when she stepsin the door, or the five-star bistro that keeps anniversaries on file and surprises couples withchampagne - both of these establishments are personalization masters.

It’s clear that consumers expect personalization in their e-commerce, entertainment, and diningexperiences. Some restaurant customers already enjoy simple personalization like birthday, joinanniversary, or new member activity status messages. Ultimately, the service experience willintegrate data-driven personalization throughout in-store and digital environments.

We hope we’ve succeeded in demystifying the difficulties restaurants face when bringingpersonalization to market, and given you some clear steps you can take now to begin building yourpersonalization plan. The future may be personalized restaurants, where each step of therestaurant experience meets individual customer needs, bringing the overall brand promise alive inindividually relevant ways. Personica’s goal is to help all restaurant teams consistently and easilyserve up five-star, personalized guest experiences.

THE 3D MODELCONCLUSION

With the growth of our Engage marketing and customer data platform,Personica is exploring the edge of what is currently possible forrestaurant personalization, and pushing the boundaries toward what’snext. We’re incorporating the 3Ds into every piece of our platformdevelopment, and are looking forward to partnering with restaurantswho want to create a personalization engine that connects allcustomer experiences - from first sign up through each campaign andtransaction.

THE 3D MODELABOUTPERSONICA

Appendix

Sources:¹ https://www.personica.com/case-study-using-personalization-and-data-to-boost-conversion-rates/² Twilio-Segment, State of Personalization Study -- Consumer (n=2700) and Business (n=300), US,UK, Aus, NZ, 2021³ https://stories.starbucks.com/press/2020/starbucks-reports-q4-fiscal-2020-results/⁴ BCG-Google, Business Impact of Personalization in Retail Study – Customer Survey (n=3,144), US,2019⁵ McKinsey & Company COVID-19 US Consumer Pulse Survey 6/15–6/21/2020, n = 2,006, sampledand weighted to match the US general population 18+ years⁶ McKinsey & Company COVID-19 US Consumer Pulse Survey, conducted globally 9/18–9/30/2020⁷ https://www.incisiv.com/report-limited-service-restaurant-digital-maturity-benchmark-2020?utm_campaign=Restaurant%20Benchmark%202020&utm_source=Ketner%20Group&utm_medium=Press%20release&utm_content=Ketner%20group%20promo⁸ https://upserve.com/restaurant-insider/digital-marketing-restaurants/⁹ https://www.epsilon.com/us/about-us/pressroom/new-epsilon-research-indicates-80-of-consumers-are-more-likely-to-make-a-purchase-when-brands-offer-personalized-experiences¹⁰ https://marker.medium.com/starbucks-isnt-a-coffee-company-its-a-data-technology-business-ddd9b397d83e

https://stories.starbucks.com/press/2020/starbucks-reports-q4-fiscal-2020-results/

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