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(Un)Structure the Omni-channel Customer Offer

(Un)Structure the Omni-channel Customer Offer
April 24, 2017

Outlining a “Flexible Customer Offer” blueprint can be a key driver for sustained Omni-channel growth

Follow the Savvy Customer: From Demographics to Context

While initial e-commerce growth has largely been fuelled by expanding the product assortment available to online customers, followed by competitive pricing and quicker deliveries, the key factor contributing to Omni-channel success is customer-centricity.

While migrating to an Omni-channel ecosystem, modern retailers and consumer brands must focus on identifying evolving customer expectations and build a suitable Omni-channel customer offer.

Each individual consumer approaches the marketplace with her own set of needs and desires, which vary based on the product category, channel, and context. She expects the retailer or brand to understand these expectations and quickly display available choices.

Amazon and Netflix have been poster children for personalization. Amazon led the pack – with its ability to create different home pages for different customers, based on their past clickstream paths or purchase history. Netflix’s rating engine recommends better movies based on ‘clustering’ technology, and envisages a point where it can completely replace its navigation grid with highly powerful and contextual suggestions of 3 to 4 videos only – simplifying choices for the viewers.

The channels and modes of interaction for a retailer are increasingly driven by the preference and convenience of targeted customers. A tech-savvy millennial prefers WhatsApp or Messenger, whereas a baby-boomer expects a non-intrusive email.

And that’s become table stakes now. 21st century consumers are far savvier, with little tolerance for generic, non-tailored interactions.

As a result, retailers need to adopt a dynamic, persona-based and context-led approach to crafting the perfect customer journey. They must build a funnel that begins with a broad customer base – across a wide spectrum of personas, needs, and sub-categories.

Retailers need to adopt a persona-based & context-based approach to curate channel experiences for the consumer

This is over and above larger buyer preferences and priorities, such as channels and product categories. The key is to rethink the “one-size-fits-all” approach that most retailers adopt while blueprinting their Omni-channel strategy.

Building Flexibility into the Customer Offer

A retailers’ Omni-channel strategy should emphasize resilience in the customer journey, creating depth of choices within each dimension of the offer. Offer dimensions cut across assortment available, delivery speed, payment or financing choices, notification methods and so on.

Different personas want a different mix of options and disruptive companies are already addressing these needs at different levels. Jet.com’s 'Smart Cart’ lets value-conscious customers gain from buying incrementally higher quantities (v/s the whole case), by debit card (v/s more expensive credit card) and forgo returns (v/s free returns) or any combination thereof. Each decision towards a value-conscious choice translates into additional pennies saved in the ‘Smart Cart’. Compare this with the premium Amazon Prime experience, and you get the picture.

For a retailer or consumer brand addressing a broader set of customers (such as senior citizens, baby boomers, and millennials), it’s not only essential to expand the offer depth, but also to quickly adapt the experience to a specific customer context during the buying journey. This creates personal, 1:1 interactions that help build a broader and more sustainable funnel.

To start with, the choices enabled on your Omni-channel roadmap need to encompass demands across all customer personas – say, senior citizens, baby boomers, millennials, and other spectrums you aspire to address.

In fact, customers from the same demographics can have different expectations from each interaction: some are there to purchase for themselves, others for their loved ones, and others are simply doing research, while some might be trying to get a job with you! Besides, there are first-time visitors and returning buyers.

There is also the case of personalization at multiple levels of a channel, such as an e-commerce website. These levels include – page layout, product content (description, price, promotions) and notifications sent to the customer through different channels (email, text, and so on).

Some customers convert better with a cleaner layout with big font sizes, while others such as millennials are ‘information-hungry’ and can consume multiple rich streams of content running together. Gmail, for instance, offers multiple choices to personalize the Inbox layout (Primary/Secondary or Social/Promotional) as well as the look and feel in which the emails are to be read.

Advances in AI are Making Hyper-Personalization Possible

The future of personalisation will be context-driven. A senior citizen’s experience when buying a toy for his granddaughter, is different from a millennial trying to purchase the same. The supporting content becomes critical in influencing the journey. While safety instructions are important for the grandparent, millennials would primarily look at catchy videos.

The choice of journey offered to the customer needs to be a function of past information – demographics, geography, history, frequency – as well as data streams captured via interactions during the current journey – location, IP address, keywords, session duration, and intensity.

Recent advances in AI technology have made it possible to churn all the historical, real-time and external data and incrementally improve response relevance via machine learning. This used to be a major challenge with the rule-based approach. Retailers can now achieve true “Mass Customization” of customer experience across the multiple nodes of the purchase journey.

Some upcoming start-ups are harnessing these advances to completely rethink their offerings. Online fashion retailer Stitch Fix provides a styling subscription service – using AI to tailor clothing and accessories for the modern woman's taste, budget, and lifestyle. The personalization is so deep that no two customers have ever received identical shipments.

Conversational commerce techniques powered by AI are also helping achieve 1:1 personalization. 1-800-flowers.com hyper-personalized its online shopping experience using “GWYN”, an AI-powered intuitive gift concierge. 

On a similar note, Macy's has been testing a mobile companion tool “Macy’s On Call” that aims to preempt users’ mobile queries with AI response. The tool enables shoppers to get answers based on the store where they are physically shopping, rather than having to find a sales associate.

It’s best for these signals to be “anticipated” and their impact proactively blended into the journey rather than expecting the customer to explicitly “subscribe” to preferences!

A Case for Blueprinting a “Flexible Customer Offer”

Blueprinting

Creating a flexible, personalized and relevant customer experiences driven by real-time data (from both internal and external sources) is now possible for an ever-growing set of customer personas – and at a scale that’s bigger than ever before.

Advances in AI coupled with commercially available technologies, present an opportunity to rethink customer experience. As a result, retailers and brands can improve the topline with “Flexible Customer Offer” blueprints.

Know more about HCL’s retail solutions and services.