The key to maximizing the customer experience, and by extension revenue, hinges on delivering contextual and relevant communications through real time customer engagement. But for many retailers, this means engaging with tens of thousands of customers making online purchases via laptops, desktop and mobile devices, as well as in-store shoppers.
So, how can retailers scale efforts to provide truly personalized omnichannel experiences to each and every shopper? Delivering personalization at scale is feasible through artificial intelligence and advanced analytics, and in this post we’ll explain how.
Omnichannel personalization is the key to winning customers and loyalty
Customers aren’t loyal to brands like in the past, and today they’re driven by price, convenience and speed of delivery. When one retailer does this better than another, game over for the latter retailer.
That’s not to say customers won’t ever be loyal but, retailers have to make it worth their customers’ time.
Fortunately, there’s omnichannel personalization, a series of practices that are designed around the customer, rather than marketing channels. By taking into consideration the customer’s buying preferences, location and other important information, retailers can make sure every interaction with an individual is tailored specifically to them.
The result? Incentivized loyalty.
To achieve omnichannel personalization, retailers have to continuously deliver relevant messaging to customers. This requires:
- Measuring customer data constantly
- Refining customer interactions based on new data findings
- Encouraging customers to engage in compelling ways
To do this at scale, retailers must adopt new tools that manage and analyze massive amounts of customer data to deliver specialized outcomes for each individual. Fortunately, AI and advanced analytics does just that.
How AI and advanced analytics make omnichannel effectiveness possible
AI and advanced analytics takes big data and identifies patterns at the aggregate and individual customer levels to answer questions such as, how will price changes affect sales, and which customers are likely to purchase your newest products?
For omnichannel marketing, AI advanced analytics specifically advances:
- Building comprehensive customer profiles that provide the insights needed to decide which offers to present to customers
- Automating messaging delivery to customers in a logical, but personalized manner. For example, letting customers know when a product they liked is back in stock
- Presenting company personnel, like customer support reps, with all of the activity the customer had with the brand, regardless of channel
- Scaling the delivery of personalized messaging
Examples of delivered personalized content
With the right tools in place, a retailer can more realistically deliver omnichannel experiences. There are many ways to leverage personalization, including:
- Basket abandonment emails to remind potential customers of products they may have forgotten about
- Newsletter and promotional emails that feature and recommend products that appeal to each customer
- Cross-selling and upselling items, as customers browse retailer websites and add items to their carts
- Text messages to alert customers of new promotions or products
It’s important to note, retailers shouldn’t exclusively use customer data when delivering personalized experiences, and indicators like city, location and local weather can be used to put specific products in front of website visitors. Together, these efforts form a personalized omnichannel experience for each and every customer.
Achieving omnichannel effectiveness is possible. And worth it.
Wherever your customers are, and however they’re interacting with your brand, through omnichannel marketing, every single one of them can have a totally unique experience. And this undertaking is worth the effort — a recent Econsultancy report found that 93% of companies saw an increase in conversion rates following personalization efforts.
So, are you ready to start better leveraging personalization?