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Personalization at scale for retailers: The journey from one-to-all to one-to-one.

If you attend a technology conference, look at social media, or read the latest posts by retail visionaries, you’ll likely be inspired to create hyper-personalized, super-astounding one-to-one experiences, driven by the latest artificial intelligence and informed by nuanced data across every step of the customer journey. And you should be inspired. The possibilities for personalization at scale in retail are immense and growing quickly.

However, it’s important for retailers not to get ahead of themselves. A number of key elements — around technology, data, and organizational structure, to name a few — must be thoroughly addressed to achieve personalization at scale. And when it comes to personalization, it’s better to do the basics well than to shoot for the astounding and miss. According to a 2017 survey from Accenture, 41 percent of U.S. consumers said they’d switched companies because of “poor personalization and lack of trust.” If you’ve ever been misidentified — say, as a trendy teenager when you’re an outdoor-loving adult — you know the feeling.


Start where you are.

Retailers who succeed at personalization at scale are honest with themselves about their current state. And they often achieve that understanding by assessing key dimensions critical for personalization at scale. If you’re one of these truth-seeking retailers, here are some things to consider:

Data and reporting intelligence

Data and reporting intelligence.
You’ll have to assess how advanced you are with gathering, incorporating, and effectively using data. Are you still unsure how to measure the success of personalization? Or are you ahead of the curve, with unified customer data across channels and integrated second- and third-party data?

Creative and content management

Creative and content management.
Personalization at scale requires content at scale, so you need to know how well you’re prepared to achieve that. Are you still using old-school workflows, full of inefficient handoffs and long email chains, or are you already able to dynamically assemble content?
 

Personalization, optimization, and delivery

Personalization, optimization, and delivery.
This is the heart of it, covering everything from targeting customers to delivery across channels. So what personalization level are you currently? One-to-everyone, one-to-few, or one-to-one? And what’s your capability for delivering personalization everywhere, whether online, in-store, in your mobile app, or on a paid video channel?

Organization and operating model

Organization and operating model.
Finally, for personalization at scale to succeed, retailers often have to change how they work. Has your organization gone through a successful digital transformation, or does it still rely on legacy models that’ll hinder its ability to deliver personalization at scale?

If, after you assess your current state, you find that you’ve got numerous challenges to achieving personalization at scale, realize you’re not alone. A large percentage of retailers are in a similar situation.


Personalization maturity — and immaturity.

A survey of retailer personalization maturity level across specific channels.

Personalization maturity survey chart
Source: RIS

First steps forward.

For retailers just beginning their journey, the first step can be simple rules-based personalization. Using this approach, a single data point — such as “new visitor” versus “return visitor” — can be turned into a targeted experience. For instance, your website could prominently feature a product a customer has viewed before, which streamlines their purchase of that product.

Geo-targeted experiences are another potential first step for retailers. For example, a clothing retailer might vary what it showcases on its home page, based on whether the visitor is from a warmer or colder region of the country.

This level of rules-based personalization can be achieved quickly and economically. With Adobe Target, for example, it can require little more than an initial setup and a few lines of code.


Stepping up your personalization game.

Adobe Target is also an engine for more sophisticated, automated personalization at scale across channels. Among its many advanced personalization options is the ability to automatically identify and target the minority of customers that make up the majority of a retailer’s sales — the customer with the proclivity to buy higher-end, larger-margin items regularly, for example. It can then automatically serve up the offers most likely to move that customer to purchase.

However, for retailers to get to the often mentioned yet rarely achieved goal of “right place, right time, right message” personalization at scale, a number of factors must come together. For example, it requires a single view of the customer’s data and interactions, both online and offline. It also demands messages and experiences be served up via the best channels, which requires well-orchestrated technology.

This is where a unified digital foundation becomes essential. Content management systems, analytics, data management platforms, advertising platforms, even creative execution tools — the more these are connected, the greater personalization at scale retailers can achieve.


“The Forrester Wave™: Enterprise Marketing Software Suites (EMSS) Q1 2018” report
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Multi-colored blobs

Out-personalizing your competitors.

Now, back to those visionary ideas around personalization at scale in retail. Although not every retailer is ready for cutting-edge AI-driven personalization at scale, some are — and it’s increasingly how they’re breaking out from the scrum.

Adobe is leading the way in next-gen personalization at scale. Just as importantly, we’re adapting it to the specific needs of retailers. For example, at NRF 2018, we previewed something brewing in our research labs — the ability to segment and message customers inside a store. This will allow retailers to identify in-store shoppers based on qualities such as loyalty, last visit date, or shopping preferences — and then push real-time in-store offers within the retailer’s mobile app based on that data.

Our AI framework, Adobe Sensei, is not only rapidly expanding the possibilities for retail experiences, it’s also streamlining and improving how they’re created. For example, the Sensei-powered Smart Crop intelligently detects and crops the focal point in any image, automatically adapting that image to each and every screen size. This streamlines the content creation process for retailers, which is essential to achieving personalization at scale.

In the next article in this series, we’ll dig into the many ways retailers are turning AI and machine learning into high-performing, brand-building, and loyalty-enhancing personalization at scale — and how they’re driving the next era of personalization at scale for retailers.

Read the next article in our series, "Artificial intelligence, authentic retail personalization at scale."



YOUR NEXT STEPS