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Personalization: how to get ready for it?

Personalization will be the prime driver of marketing success within five years. Here are the capabilities companies need to develop to stay ahead of the curve.

The exciting promise of personalization may not be here yet (at least not at scale), but it’s not far off. Advances in technology, data, and analytics will soon allow marketers to create much more personal and “human” experiences across moments, channels, and buying stages. Physical spaces will be re-conceived, and customer journeys will be supported far beyond a brand’s front door.

Positioning businesses to win requires understanding the three main shifts in personalization and building up the necessary skills and capabilities to respond to them.

Physical spaces will be ‘digitized’

AI technology – One area where the implications could be significant is in store visits. Some retailers have already started down this path to move beyond established, though still rudimentary, personalization practices. At a cosmetics group’s flagship store, an AI-powered program, enabled by Google’s conversational Dialogflow platform, directs customers, while augmented-reality glam stations let customers “virtually try” products—by altering the customer’s image as if the product has been applied. But this doesn’t mean the end of the salesperson or stylist.

These virtual experiences still need the human touch. The cosmetic’s stations still need customers to tell stylists what products they’d like to try. As AI evolves, systems can generate recommendations based on analyzing a customer’s skin tone, facial features, and emotions in real time to tailor what to recommend or avoid offering.

READ MORE Personalized Pricing through AI

GPS technology – Macy’s, Starbucks, and Sephora are using GPS technology and company apps to trigger relevant in-app offers when customers near a store. Other retailers have begun to provide sales associates with apps that generate personalized product recommendations for specific customers automatically. One retailer found an app like this generated a 10 percent lift in incremental sales and a 5 percent increase in transaction-size growth.

The next level of in-store personalization is likely to include providing these kinds of experiences to all customers as well as pulling in more advanced AR features to help customers experience products and services in different environments, such as trying hiking boots on a “virtual mountain.”

Empathy will scale

Understanding social cues and adapting to them is how people build trust. That’s not easy to do digitally or at scale. Machine learning is changing that, or at least getting much better at reading and reacting to emotional cues. More sophisticated algorithms are allowing programs to interpret new kinds of data (visual, auditory) and extrapolate emotions much more effectively than in the past.
Amazon has patented new features that will enable its Echo device to detect when someone is ill—such as nasal tones that indicate a stuffed nose. It will then offer a suitable recommendation, such as a chicken-soup recipe or cough drops, some of which could then be purchased over the device for at-home delivery.
Other companies are getting into the game too. Affectiva, which spun off from work scientists were doing at the MIT Media Lab, is using machine learning to develop emotion-recognition algorithms to classify and map facial expressions, such as anger, contempt, disgust, fear, and joy.

Ecosystems to personalize journeys end-to-end

Different providers jointly own the customer experience.
A mall operator, retail store, and brand product, for instance, all contribute to a shopper’s buying experience. But each sees and affects only a portion of the total buying experience. Creating connections between those points represents a big opportunity in the next level of personalization, as expanding partner ecosystems allow brands to provide more seamless and consistent consumer experiences across all stages of their decision journeys. As AI gets better at predicting consumer needs – turning on the lights or turning up the heat shortly before someone comes home – personalization programs can navigate the transition from one system (car) to the next (home lights or home furnace).

Industries as diverse as banking, healthcare, and retail are also forging ecosystems comprising a variety of businesses from different sectors to improve customer service and expand the quality and array of solutions offered.

READ MORE Retail, a Digital Shift to Omnichannel Marketing

How to turn the future into reality

Personalization tends to be thought of as an important capability for marketing, but we believe it must become the core driver of how companies do marketing. Here’s where brands need to focus now:

Invest in customer data and analytics foundations
  • Personalization is impossible if marketers don’t have the means to understand the needs of high-value customers on an ongoing basis. So top marketers are developing systems that can pool and analyze structured and unstructured data, algorithms that can identify behavioral patterns and customer propensity, and analysis capabilities to feed that information into easy-touse dashboards.
  • Setting up a centralized customer-data platform (CDP) to unify paid and owned data from across channels is essential to these efforts. Unlike traditional CRM solutions, CDPs provide built-in machine-learning automation that can cleanse internal and external data, connect a single customer across devices, cookies, and ad networks, and enable real-time campaign execution across touchpoints and channels.
  • Individualizing outreach across channels also requires companies to develop and interact with new sorts of data, from voice to visual. The best are already actively experimenting with these technologies by developing use cases to understand how to best use them.
  • Making this technological leap forward requires marketing and IT to join forces. A product-management team, with representation from both IT and marketing, should be established to build and refresh the organization’s martech (Marketing technology) road map, develop use cases, track pilot performance, and compile a robust library of standards and lessons learned. MarTech engineering should deliver needed capabilities to the team, including cybersecurity systems able to keep pace with the expansion of personalized experiences.
Find and train translators and advanced tech talent
  • Personalizing spaces, moments, and ecosystems will require very different skill sets from those of the traditional marketing operation today. In addition to data scientists and engineers, marketing organizations will need analytics translators who can communicate business goals to tech stakeholders and data-driven outcomes to the business. As data become more complex and personalization use cases more advanced, the need for these translators will intensify.
  • Not surprisingly, the battle for AI talent will escalate. While organizations will need to figure out which talent to hire (those with core capabilities to drive creative problem solving) and which to access through an ecosystem of external talent, leading companies are moving aggressively to acquire relevant talent.
  • The buildup of relevant tech talent will need to be matched by improved training so that people throughout the organization understand not just how to use new personalization tools but also how they can help them make better decisions.
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Build up agile capabilities
  • Given the iterative, cross-disciplinary nature of personalization efforts, traditional siloed marketing teams won’t work. Instead, personalization requires a commitment to agile management, including cross-functional teams dedicated to specific customer segments or journeys with the ability to execute rapidly.
  • In addition to demonstrating needed expertise, the ability to collaborate and integrate information will be key to professional advancement. Equally important will be the ability to collaborate and solve problems with colleagues from across the organization, in IT, analytics, product development, and legal.
Protect customer privacy

Privacy issues lie at the heart of the trust between customer and brand. Companies need to get it right.

  • The nature of data privacy has rightly become a source of concern for consumers and brands alike. Companies at the cutting edge of personalization innovation are more likely to—rightfully or not—trigger privacy concerns among the customer base. As such, proactively managing customer privacy will be especially important.
  • Organizations need to go out of their way to make clear that they take data privacy seriously, by being transparent about how data will be used, limiting processing of personal data to what is necessary, protecting data against theft, and granting customers the right to be forgotten.

Developing a personalization capability is a journey to get to the full suite of capabilities needed for true dynamic personalization: always-on, real-time, one-to-one communication across the consumer ecosystem.
The first step is to determine which use cases to focus on (converting new customers, increasing spend of loyal customers, etc.) and put an agile team on each of them to rapidly test and learn which offers and interactions best deliver.