The Ultimate Guide to Personalization

Personalization is a hot topic in digital and the potential benefits of a cross-channel, consistent experience that adapts to customers as their needs and goals change are huge. However, personalization is also a topic that brings some confusion as the proliferation of fragmented technologies offering very different levels of personalization means that there is no clear definition on what a personalized customer experience really entails.

The Guide to Delivering True Personalization 2

72% $400M

2017 2018

Increase in business technology spending1

Firms are leveraging new technologies to win, serve and retain customers better.

“personalizing the customer experience”

of global eBusiness and channel strategy professionals consider

as a major opportunity to improve in-store experiences.

However, in the same survey 53% of digital experience delivery professionals said they lack the right technology to personalize experiences.2

Potential revenue loss for not offering a positive, consistent, and brand-relevant customer experience, according to executives3.

or 20% annual revenue for a B2B brand.

9% 8.4%

CONSIDERA FEW STATISTICS

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The heart of personalization is goal attainment. Importantly, these goals should be customer driven. It’s not about simply delivering what your business wants but about allowing every visitor to consume the experience how they prefer and helping them achieve their goals from moment to moment.

Think of a business you interact with online—your favorite store, your bank, a vacation booking site—and recall the variety of goals you’ve looked to accomplish there. Your needs from a home goods store may be quite different during wedding season, you relied on your bank for a new set of information when buying a home, and your vacation preferences change depending on if you are traveling by yourself or with family. Each visitor interacts with businesses in a multitude of ways and truly powerful personalization looks beyond who you are to what you are trying to achieve right now.

Of course, this is easier said than done. While personalization is an increasingly hot topic, most businesses are still in the early stages of understanding how to best utilize it. When embarking on a new personalization strategy, or revamping an existing one, personalization boils down to three main questions:

1. Where should personalization occur in the experience?

2. What information will be used to create a personal experience?

3. How will you use technology and human insights to create this personalization?

WHAT PERSONALIZATIONSHOULD BE

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A major issue that digital business faces when discussing personalization is that there is no single tactic that defines it, and each class of technology comes with limitations.

Wisdom of the Crowd

Semantic Understanding

Segmentation/ Targeting

1:1 Personalization

Technology

Leverage the behavior of many to provide an experience

Identify & recommend products/services based on content similarity

Produce different experiences for defined user segments

Create a profile for each user and uniquely tailor the experience

ExamplePeople that viewed X also viewed Y

Understanding search queries

Targeting messaging and call to actions

Providing individual recommendations, suchas product grids

Limitation

Does not adapt to the individual context of the consumer desire

Does not factor visitor history & preferences into search results

Does not create unique experiences for individual users

Requires large amount of data and is difficult to scale

COMMONLY USED PERSONALIZATION TECHNOLOGIES

PERSONALIZATIONHAS BEEN FRAGMENTED

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Real time personalization requires noticing how a visitor’s behavior differs or aligns with their typical behavior, identifying their current goal through their own behavior and the behavior of similar users, and using insights across all levels of technologies to help them accomplish this goal.

THE SPECTRUM OF PERSONALIZATION

HUMAN MACHINE

1:1PERSONALIZATION

WISDOM OFTHE CROWD

SEMANTICUNDERSTANDING

SEGMENTATION& TARGETING

Each one of these technologies is on the spectrum of personalization, and the way forward is to combine each of these technologies to build a comprehensive intelligence around user intent. To get your visitors to their goal of the moment you need to understand them and tailor your experience across every level these technologies offers.

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Today, personalization is happening around the edges of the user experience. Small variations here and there, driven by widgets or add-ons, that are often controlled by separate teams within the company. To realize the promise of personalization, this setup needs to change. Personalization needs to be built into the core of the experience and impact every point of interaction. Site search, browsing data, product recommendations, landing pages, and all other interaction points should work cohesively to build a complete picture of each visitor across their journey.

This level of cohesion is only possible when the data-churning engine lies at

the heart of the experience and can power every visitor touchpoint from websites to in-store kiosks. So much of today’s personalization efforts are done around the fringes of the website, with one tool running product grids, another running A/B tests on banners, and another targeting content by location. When all these solutions are simply tacked onto the experience, the data doesn’t talk and personalization is fragmented and doomed to stay on the fringes. Having a platform with native, intelligent personalization built in allows you to gather data from multiple touchpoints and combine it in one central location.

Recommendation Widget

A/B Testing Widget

Before: When personalization is controlled by separate tools with no data connectivity it can only occur on the fringes of the experience.

PERSONALIZATION NEEDS TO BE AT THE CORE OF EXPERIENCE

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Centralizing this data enables personalization to go beyond the fringes and deliver far more holistic experience that spans across the entire spectrum of brand interaction. Data gleaned from visitor search, page navigation, product preference, multi-channel usage, and external data from CRM systems can combine with larger picture data on product performance and user personas to gain deeper insights into how your customers prefer to interact with your brand experience. These insights, combined with the scalable power of machine learning, can help you deliver a 360 experience to every visitor.

Having this engine at the core of the experience also allows businesses to get the full value out of third party software,such as Customer Relationship Management,marketing automation, social media and all other data collection points. When the digital experience is built with native personalization open to APIs, third party solutions can feed data directly into the core engine. Allowing for the un-siloing of data, technologies and, importantly, the teams focused on different aspect of the experience.

Multi-channel Usage

Page Navigation Visitor Search

After: Centralizing data at the core of the experience lets the entire spectrum of personalization interact.

Product Preference External Data from CRM Systems

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Advancements in technology, especially the increasing accessibility of artificial intelligence (AI), has been a major driver of personalization. The correlation between the two can lead to polarizing opinions on who, or what, should own the personal experience. For example, one side may argue that algorithms should be wholly in charge of ranking products on a category page and that any human interference would dilute the optimization. The counter argument is that a machine could never match the understanding a seasoned business user has of the nuances and trends in the industry and customer desires. This argument often accompanies the concern that machines are being set up to replace the people that run merchandising or marketing.

Both of these views are extreme. The resulting reaction is often a fear of being replaced. This holds people back from seeing the benefits of utilizing machines for what they do best and allowing themselves more time for human creativity.

Speed

Scalability

PatternRecognition

No bias

Creativity

Contextualunderstanding

Ethics

Machines can crunch data quickly, enabling real time optimizations and scalability. But there are definite limitations to how far the math of machines can take the experience:

• Machines are only as good as the data they’re fed. They are limited to the sources and type of data they can collect. They lack the creative ability to make connections that require life experience beyond data.

• Machines are limited to the amount and time duration of the data collected. They require a large amount of data to recognize and adjust to trends. They can only make decisions on the scope of data they have in the moment, whereas humans can rely on past and current knowledge to immediately identify and react to cultural and industry trends.

• Machines do not react well when multiple variables change at once. If an event causes sudden irregular behavior, such as an item going on sale and receiving an influx of purchases, the machine will have a difficult time understanding and reacting to this sudden change in behavior.

HUMAN + MACHINE

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Truly creative solutions require more than data, they require real world experience and application of industry, customer, and cultural understanding. For example, a clothing retailer knows that customers will soon be looking for festival wear. They create a landing page and add in the products they believe festival goers will be hunting for. The machine then gets to work, boosting items that are performing well, have more stock available, and align to the visitors preferences. Additionally, content marketers might create targeted inspirational content around regional festivals and let the machine provide the right content based on IP locations.

Adding intelligence to the user experience can also provide real time assistance to users that simply isn’t possible manually. For instance, say a transportation service

HOW TECHNOLOGY AND HUMANCREATIVITY COME TOGETHER

has an app offering public transportation directions. Algorithms could determine, based travel speed, if the user is walking, biking, or driving, and recalculate the journey with the appropriate timings.

For organization who rely heavily on content, intelligence can help direct the creation of that content by identifying gaps in information that visitors are searching for. Perhaps a financial company sees a rise in visitors searching for information around automating investments - information like this can help content creators prioritize the rising topics their actual customers are interested in. Through natural language processing and machine learning these trending topics can be identified quickly, without the hours of manpower that would be required to read through thousands of search terms and pull out trends.

Truly creative solutions require more than data, they require real world experience and application of industry, customer, and cultural understanding.

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A new person comes on to the website. Immediately, you can use data from sources such as geographic location, browser, device, and databases (such as matching their IP address to a company name) to begin to optimize the experience. You can look to click behavior to start to derive interests and introduce them into different segmentations.

For BloomReach customers in particular, the issue of cold start can be eliminated by applying wisdom of the crowd right away, thanks to the large amounts of user preference we have across industries.

The visitor returns to your site and now expects a more relevant experience. You already recognize the information derived from their previous visits and perhaps they gave further information while on the site - such as filling out a form, click behavior, or search history - that showed an interest in a particular product. This information can be used to further segment the products and content delivered.

As the visitor interacts more frequently, BloomReach uses pattern detection to connect un-logged in visitors across multiple devices using a number of behavioral and technical signals. For instance, if devices on one Wi-Fi network viewed the same category page and three product pages over a two-day period, there’s a high probability that it is the same person. This cross-channel information is combined with the increasing understanding we have of the individual to deliver an enriched and continuous experienced across touchpoints.

The visitor has opted into giving details about their identity and preference, such as through creating an account. These preferences should be used to shape all communications with them through 1:1 personalization. Marketers and merchandisers can use this deep level of visitor information to assess and update their strategies and processes in cycle of continual improvement across each stage in the customer path.

From Anonymous to Advocate

The goal of personalization is to engage each customer for the entire relationship, from first interaction to recommending your brand to others. By incorporating the whole spectrum of technologies and personal insight at different customer stages, businesses can build a 360 view of the customer to tailor the experience every step of the way.

Anonymous Visitor

The Known Visitor

The Advocate

FROM ANONYMOUSTO ADVOCATE

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Personalization technology should be comprehensive

To bring visitors through these stages, it’s important to know what information can be used, and how best to leverage it. This reflects back on the spectrum of personalization, and the importance of having a core instance where the data across the entire spectrum comes together. Bringing together wisdom of the crowd, segmentation, and individual user data means visitors can seamlessly travel from their first visit to brand loyalty.

SegmentTargeting

1 to 1Personalization

Wisdom of the Crowds

CONTENT(SEMANTIC)CHANNEL

USERS SITESTRUCTURE

Intent

Journey

Content Performance

Page/SitePerformance

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Analysis: Evaluate the performance of your experiences looking at key performance indicators across all of your customers.

Insight: Find clear opportunities and hypothesize strategies to improve your customers’ experiences.

Act: Incorporate your strategies into the experience by pairing human insights with scalable machine technology.

Evaluate: Evaluate your hypotheses against a baseline to determine whether they have improved the experience as intended.

To bring your customers the tailored engagement that personalization promises, marketers and merchandisers must continuously monitor and use the data to tweak the experience in a continuous cycle of improvement. Using this, businesses can quickly experiment with and tweak their strategy to determine what parts of the experience show the most impact to visitor engagement and revenue. It can help marketers determine exactly where in the experience they should focus efforts.

The Continuous Cycle of Improvement

LISTENING TOAUDIENCE & KPIs

EVALUATEHYPOTHESIS

FIND OPPORTUNITIES& HYPOTHESIZE

STRATEGIES

TEST STRATEGIES VIAMACHINE & HUMAN

INTELLIGENCE

ANALYSIS. INSIGHT. ACT. EVALUATE.(Cycles of Continued Improvement)

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Resources1. US Tech Market Outlook For 2017 And 2018: Mostly Sunny, With Clouds And Chance Of Rain; 2. The Top Retail Technologies To Watch In 2017; 3. Oracle Global Insights on Competing in the Customer Experience Era

Search returns the most relevant products to your audience, ranked according to performance and each visitor’s’ personal behavior. Our continuously learning technology ensures your visitors automatically receive the most relevant results, while also giving you control to manually adjust product rankings to respond to known trends, events, or upcoming promotions.

Easily curate and scale product listing pages that fit your brand, marketing, and performance goals. Dynamic, visual merchandising controls make it simple to balance any number of product ranking goals across multiple sites. Manually create top category and editorial pages while letting intelligent algorithms personalize the rest at scale.

Native tracking and testing allows you to continuously observe the effects of your changes on revenue, conversion, and customer engagement.

Insights uses natural language pro-cessing to understand the real lan-guage your customers are using to identify spots of improvement in site navigation, troubleshoot site search issues and provide conver-sion-boosting site improvements.

Combining product performance data and user behavior, Insights pinpoints the issues that are pre-venting customers from converting and provides immediate advice on how to fix these issues to help guide each customer to the products they are interested in.

With BloomReach Personalization your team will understand more than just sales, they will understand which products your customers prefer together, the language they use to discover products, and a deep view of their customer journey across online and offline interactions.

BloomReach Personalization is a single place where your team can take fast, measurable revenue-driving actions that personalize cross-channel customer experiences at scale.

Advanced algorithms drive the whole spectrum of personalization and power a full set of tools including:• predictive insights• visual merchandising• measurable targeting• testing

It enables merchandising and search teams to create and test intelligent, personalized and revenue-driving customer browse, search and landing page experiences by pairing AI with smart, intuitive merchandising tools and analytics.

Search Merchandising Insights

BLOOMREACHPERSONALIZATION