What exactly is personalization? Contextual customer experiences are no longer a “nice to have” in today’s highly competitive marketplace; they are a “must-have”. While nearly every retailer today promises to “personalize” their shopper’s experience, just a handful do it correctly. Most of the time, these discussions revolve around topics such as:
- How should an ideal personalized experience look?
- How can you personalize the retail customer experience?
- How do you personalize the in-store experience?
- What is eCommerce personalization?
- How can you blur the boundaries of E-commerce and In-store personalization?
Current state of personalization
What’s going on here?
According to Mckinsey research, 71% of customers want businesses to provide individualised interactions. And 76% are dissatisfied when this does not occur. Adding to the pressure on businesses, if customers don’t like the experience they’re getting, it’s easier than ever for them to switch to something else. During the pandemic, three-quarters of consumers moved to a different retailer, product, or purchasing method.
Retail personalization enabled by AI provides each consumer with a 1:1 experience that is tailored for more engagement and higher conversion. Good data is the prerequisite to personalization in retail. Here’s how data can help create personalized retail experiences:
- Shopper profiles
- Behavioural cues
- Transactional data
- Demographic data
- Unified retail personalization (Which strikes a balance between data-driven algorithms and real-time contextual events in a shopper’s history)
It not only provides insights for visual merchandising, but it also influences buyers’ decisions to buy products for the upcoming season.
Personalization engine must be sensitive to changes in browsing and purchasing habits caused by life events. This comes down to determining a shopper’s real objective.
Contextual Shopper Intelligence
Contextually intelligent systems enable firms to deliver personal data, interaction history, and other parts of the customer journey to contact centre agents. Contextually intelligent solutions save consumers from having to repeat themselves and, as a result, contribute to greater experiences.
While a good retail personalization engine can recognise visual and non-visual indications to create shopper profiles for each consumer, it needs to be combined with contextual shopper intelligence to provide the right product at the right time to the right shopper. Here are different types of product recommendations you can offer your consumers:
Today, eCommerce retailers deploy a range of product recommendations across channels and at various stages of the shopper experience.
They are roughly classified into three categories.
- Global Recommendations – These suggestions are based on worldwide trends and perspectives.
- Contextual Recommendations – Product affinities are used to make contextual recommendations.
- Personalized recommendations – These suggestions are based on the shopper’s preferences. (browsing history, recommended visuals, dynamic personalization)
Retail Personalization across the entire shopper journey
Different recommendation strategies must be selected and optimised for each page type in order to maximise potential income.
- Homepage Personalization
- Category Page Personalization
- Product Detail Page (PDP) Personalization
- Cart Page
- Post checkout
The majority of visitors arrive to a website via the home page. The category pages, on the other hand, are for customers who are seeking a certain sort of goods but are unsure which one to purchase. A customer arrives at a product detail page because they prefer a certain product or at least the qualities of that product.
When customers add products to their cart, they have demonstrated a definite desire to purchase the item, which indicates they are more likely to buy it than if they were on the (PDP) Product Detail Page. After the buyer has purchased things from the site, the store might show more products that will tempt the shopper to return and purchase more.
Moreover, AI is an Umbrella term that is used to describe a variety of techniques like ML, NLP, and more! Watch our Fireside chat.
Without one unified (single) platform that controls everything, eCommerce retailers would require a massive crew whose primary responsibility is to personalize customer journeys. Unified commerce is intended to assist eCommerce teams in managing the massive effort of providing individualised consumer journeys that lead to growth.
Unified commerce to your retail ecosystem
The concept of unified commerce a completely integrated online and offline retail brand experience – allows retailers to combine data and present a more complete picture based on all inputs. That is why it is critical to locate a point of sale system that automatically centralises and syncs offline and online purchase data.
Creating a Unified Experience for the Customer: If a consumer has to replace their favourite shirt that they bought 2 years ago at your store, they should be able to find out exactly what variant they bought, down to the size, colour, and style.
Don’t Miss Out
This is only feasible if all data is in one place. You can also have a quick read ? 3 ways in which Unified Commerce helps B2C businesses offer hyper-personalized experiences to consumers
As unified personalization is expected to reach a large percentage of e-commerce sites over the next couple of years, we expect to see an even more customer-centric personalized shopping experience become the new normal, both online and offline.
Using a single vendor for your unified personalizations has the obvious benefit of giving your customers with a consistent experience across all channels. With each customer engagement, the personalizations improve and become more targeted, and a single vendor enables an integrated customer experience across all levels of brand interaction, free of distractions and data confusion. You can engage and delight your customers at every touchpoint if you establish a solid foundation for personalization.
Watch Krish Lakshminarayanan VP- BI and Advanced Analytics at Dine Brands and Krishnan Jayaraman, VP- Data analytics and RPA at Aspire Systems talk about how B2C businesses can adopt AI to enhance their CX across all touchpoints.
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