WHITE PAPER:

PERSONALIZATION

2.0

By: Dan Theirl Rubikloud Technologies Inc. www.rubikloud.com

Prepared by: Laura Leslie TaylorLongfield Neil Laing Martin Mark

INTRODUCTION

What is personalization 2.0 and why does it matter? Personalization in the past has been driven by segmentation. This customer segment is similar so let’s try to market all the same products and services to them. Just because a customer spent the same amount on their purchase at the same frequency as their neighbor does not mean they want to buy the same products. Why do retailers group neighbors Sarah and Olivia in the same campaign? Personalization 2.0 is driven by in-depth knowledge of the consumer, offering an individualized experience. When you head over to your barber or stylist you went to for the last 10 years, you expect them to know your name and hairstyle you prefer. That’s the feeling consumers now expect from retailers. Based on research, 86% of consumers confirmed personalization has an impact on their purchasing decisions.1 This whitepaper will discuss personalization 2.0 from many technical, human and practical levels to help retailers deliver on consumer’s demanding expectations.

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86% OF CONSUMERS CONFIRMED PERSONALIZATION HAS AN IMPACT ON THEIR PURCHASING DECISIONS

1 Infosys, “Rethinking Retail: Insights from consumers and retailers into an omni-channel shopping experience”, Infosys Limited, December 2013.

WHAT IS PERSONALIZATION 2.0?

Personalization 2.0 is not just a technology, not just product recommendations, not just a birthday reminder, and not just a buzzword. Personalization 2.0 is transforming retail back to knowing each individual customer’s wants and needs to offer a personal experience across all customer touchpoints. When you walk into your local hardware store of years past, the store owner would ask you, “How’s repainting your house going, Bob? Need a paint sprayer to make it easier? We have a great sale today.” They know you, what you are working on and anticipate what you may need, creating a personal shopping experience. The store owners are able to stock exactly what their local community needed for that period at affordable prices.

How do large chain retailers go back to offering that personal shopping experience every consumer yearns for when they have millions of customers, thousands of employees, and hundreds of stores? Big Data has changed the game enabling personalization 2.0 to happen. Finally, technology has caught up with consumer demands, enabling store associates to help each customer walking through the door, website or mobile app to find and buy the right product at the right price for them. Once a customer self-identifies who they are with a loyalty card or logging into a digital channel, a profile pops up on a screen with their name, their preferences, what they purchased in the past and recommendations on new items they should try. Simply stated, Big Data technology made specifically for enterprise retail has started to help mimic the ‘mom and pop’ store experience.

However, what the ‘mom and pop store’ does not have to deal with are multiple channels. The customer now expects to purchase any item at any point in time with a seamless experience. The recommendations made to them by the in-store associate should easily be available in their mobile experience, iPad or desktop at any time that’s convenient for them. Retailers also need to be aware of experiences outside of their company that impact their customer’s expectations. They now expect the same personal experience they receive at their coffee house as they do from their beauty store. Far too often, retail marketers only look to their direct competitors for inspiration for better customer experiences, but this is simply not sufficient anymore.

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WHY DOES IT MATTER NOW?

Consumer demands are changing across the globe largely due to Millennials becoming the largest segment of consumers by 2018. They will also command the most spending power of over USD 3.39 trillion annually.2 Millennials are starting families, purchasing houses, raising pets and living in or around urban centers. This creates an enormous opportunity for retailers to grow with this generation and enable the purchase of items they need to establish their lives and careers. The retailers that adopt to their expectations online and offline will prevail. According to Edelman Digital research, 41% of Millennials have already made purchases with smartphones while 48% of Millennials are influenced more by social media than TV ads for product purchase.3 Research suggests 62% of adults under 34 are willing to share their location for more relevant content.4 Generic mass marketing approaches are less effective with this new generation of consumers.

Retailers must transform their entire organization into a personal shopping experience in order to compete for future generations of consumers. Retail is sometimes a tumultuous business where a bad quarter could crush the entire organization under debt obligations to suppliers within a very short time period. Retailers are facing a sober choice: evolve or die. The fear of becoming the next Circuit City, Borders, or RadioShack is real.

The benefit to retailers that do take advantage of this new wave is that Personalization equates to higher margins, more customer loyalty, and higher incremental sales. Strategically, well-executed Personalization brings retailers higher retention rates, improved brand loyalty, and an increase in upselling and cross-sell value. Research by Aberdeen Group found that personalized campaigns improve click-through rates by 14% and conversion rates by 10%. In order for the transformation to occur, retailers first must understand the scope and complexity of such an undertaking, which is discussed below.

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OF MILLENNIALS HAVE MADE PURCHASES WITH

SMARTPHONES

OF MILLENNIALS ARE MORE INFLUENCED BY SOCIAL MEDIA WORD-

OF-MOUTH THAN TV ADS

OF ADULTS UNDER 34 ARE WILLING TO SHARE THEIR

LOCATION FOR MORE RELEVANT CONTENT

2 N R K Raman and Patrick Desmares, “Are Banks Ready for the Next Generation Customer?”, Oracle Financial Services Software, Efma, September 2010.

3 Alex Abraham, “By the Numbers- 50 Facts about Millennials”, Edelman Digital, 1 June 2011.4 Meghan Keaney Anderson, “Stop Being Rude: 22 Data-Backed Reasons to Personalize Your Marketing”,

Hubspot, 12 September 2013.

BUT HOW?

Everyone in the organization and every system from procurement, brand management, customer service, marketing, and executives need to embrace the mindset of knowing the customer beyond generic personas. Taking action using customer profiles with rich purchase history, preferences, customer service logs and even buying intent from social media can drive higher margins and improve customer satisfaction. These efforts in turn reduce churn rates and increase market share. Successful retailers embracing personal shopping experiences across the entire brand are among the innovators in their market. Retailers such as Sephora, Burberry, Starbucks and Nordstrom are offering their customers a better personal experience than their competitors.

The customer must become the center of the retail organization. Gathering richer data sets on each individual is a prerequisite to implementing the systems necessary to achieve the personal shopping experience across all stores and touchpoints. The retailer must provide the customer multifaceted value from the experience including rewards, how-to-guides, and special discounts. Machine learning powered models create better recommendations and individualized content over time as they digest more in-depth information and longer history from each customer. Retailers need to collect data sets rich with purchase history, demographics, geographics, device and timing preferences, internal and external online searches and similar customer profiles to fill in gaps. Further data sets for specific retailers such as birthdates, skin color, shoe size, clothing size, and hat size are essential. Location specific data sets such as weather, macroeconomic, and holiday information plays a role in the final output to shape the shopping experience.

Attempting to use the rich customer profile data to match the millions of customers with the right product, at the right price, in real time is an exponential Big Data problem. This problem requires sophisticated algorithms that parallelize across thousands of servers while providing results to the right touchpoint in milliseconds. Performing this calculation in the time needed has simply not been possible with traditional data warehouses. Traditional approaches settled on segmentation to reduce the complexity, but these approaches reduced the effectiveness of

campaigns. Big Data systems and more efficient algorithms have enabled a scalable approach for aggregating the data and computing calculations across all the disparate databases within and outside the organization. This, in turn, has allowed smart retailers to build and act on enriched customer profiles that build the foundation of Personalization 2.0 in retail.

The following graphic illustrates how these Big Data systems function within a transformed retailer:

These systems rely not only on the volume of data but more importantly, the quality over time. In order to activate data-driven personal shopping experiences, the proper collection, processing and cleansing of transaction and customer data should utilize a global customerID across all touchpoints. For example, the purchase history from an in store purchase through the POS terminals will be impossible to match up with their past online order history without it. Many retail organizations struggle with data integrity and connectivity to support this shift. Working with the right company and technology, retailers are able to overcome many of these challenges by standardizing their systems to finally communicate with one another through a global customerID.

PURCHASEHISTORYDEMOGRAPHICS GEOGRAPHICS

DEVICE &TIMING

+ PERSONAL CHARACTERISTICS: BIRTHDAY, CLOTHES SIZE...

OFFERS TO CUSTOMERS

+ EXTERNAL DATA: WEATHER, MACRO ECONOMIC...

SEARCHHISTORY

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COMMUNICATION WITH CUSTOMER IN ANY CHANNEL

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EXAMPLES OF PERSONALIZATION 2.0 PLATFORMS

To solve many of the data challenges, a new breed of technology vendors are needed for Personalization 2.0. Connecting siloed data sources from legacy systems, multiple vendors and external sources is an overwhelming IT undertaking. Many large retail organizations working with existing technology vendors and consultants take on multi-year, multi-million dollar projects to start building the foundation and infrastructure necessary to support this new data-driven approach to customer communication. Unfortunately, the vendors win and the retailers lose through the complexity and costs of these projects. The next wave of Personalization platforms need will come from innovative startups with Big Data, machine learning and retail expertise at their core to help retailers drastically improve business results and take back market share. Various platforms are needed to execute a holistic personalization strategy, some examples are listed below.

ENGAGECLICKTM

“EngageClick’s unique, adaptive advertising personalization platform uses machine learning and cognitive science to continually learn and improve ad engagement by fine-tuning personalization for each consumer over time. Gathering information about consumers and grouping them into sell-able segments has become big business. Targeting these sell-able segments in real time, in a cost-effective manner, through relevant advertising appropriate for the device, geography, time of day, etc. has not been possible until now. This is EngageClick’s unique proprietary value proposition.”5

MARKETOTM Marketo Real-Time Personalization is the first and only marketing software that can help you unify conversations across channels and generate personalized digital experiences for every individual customer and prospect. When you combine it with the rich behavioral profile and smart targeting capabilities of Marketo’s Marketing Automation, a new level of personalization is unlocked, based on individual behaviors rather than broad, pre-determined segments.6

5 Engageclick, “About Us” , EngageClick, 2014. 6 Marketo, “Create Meaningful Interactions with Prospects and Customers”, Marketo Inc, 2016.

RUBIKLOUDTM

Rubikloud Technologies Inc was founded on the principle that data was the future fuel of retail. The Rubikloud platform empowers retailers to act on their data through true 1 to 1 marketing campaigns across all channels, not just email. The platform lives in the center of the organization delivering insights, data visibility, but more importantly, output that retailers implement to drastically impact marketing campaign performance from all measures and channels.

DATA INGESTION

LOYALTY POS SEASONALITY MORE...

RUBIKLOUD’S PERSONAILIZATION

THE RUBIKLOUD PLATFORM

MULTI CHANNEL EXECUTION

PERSONALIZED RETAILERS

STARBUCKSTM

Starbucks is a leader of omnichannel marketing as a specialty drink retailer. They focused on the experience for the consumer above all else. This enabled intense brand loyalty as they expanded across the globe. In order to further provide a warm and personal experience for their consumers, they innovated early on by providing a mobile payment and awards system. The early adoption of their mobile app has provided Starbucks with an unprecedented early lead in enabling the 1 to 1 experience consumers crave and now expect. Up to 60% of consumer’s time online is now spent on mobile devices.7 Starbucks customers adopted their mobile app aggressively accounting for over 20% of their in-store purchases as of July 2015.8 Starbucks continues to offer the consumer enough value through relevant personalized offers and convenience through mobile payments that grow app adoption and brand loyalty.

BURBERRYTM

Burberry leads the way for personalized consumer experience through many different campaigns as a high fashion retailer. They have allowed customers to customize their perfume with initials on the bottle and display those personalized products in advertising campaigns helping boost sales over 55%.9 They have gone as far building specific technology that allowed customers to send kisses back and forth to each other to showcase the personal interaction between brands and customers.10 Burberry also empowers store associates with valuable information about each customer as they identify themselves through the door.

7 Brian Honigman, “Lessons Learned From Starbucks on Experimenting With Mobile Marketing at Retail”, Huffpost Business, TheHuffingtonPost.com, 4 June 2015.

8 Pymnts, “Starbucks’ Massive Mobile App Momentum”, Pymnts.com, 1st in Media LLC, 24 July 2015.9 Russell Parsons, “‘My Burberry’ personalisation boosts sales by 55%”, Marketing Week, Centaur

Communications Ltd., 14 October 2014.10 The Art, Copy & Code Team, “Burberry Kisses”, think with Google, Google, June 2015.

WHERE DOES PERSONALIZATION 2.0 LEAD US?

Personalization 2.0 is the future of 1 to 1 communications with customers across all industries. Personalization 2.0 is the culmination of Big Data systems, machine learning algorithms and consumer longing for a much more personal shopping experience.

A single data hub is needed for companies that link all customer touchpoints and preferences together to create a relevant and enjoyable experience for consumers. Rubikloud Technologies Inc is one of those rare companies that provides a single platform empowering the future of retail with more personal shopping experiences.

ABOUT RUBIKLOUD:

Rubikloud is a retail intelligence platform focused on turning retail data into revenue and actionable insights. Using modern data science techniques, we help omnichannel retailers know their customers at a deeper level. Retailers use this knowledge by communicating with their customer across all channels in a more individualized manner. We believe the most valuable insights lie at the intersection of the retailer, the customer, and the brand. Most legacy analytics systems are unable to process, analyze and act on insights from multiple channels. Rubikloud is able to do all these things and deliver results via our proprietary platform - RUDITM.

About the Author: The author has over 10 years of experience helping retailers use analytics and conversion optimization tools to help them make the right data driven marketing decisions. He is now a co-founder of a Toronto based retail intelligence startup called Rubikloud.

web: www.rubikloud.comtwitter: @rubikloud