Opinions expressed in this article are those of the sponsor.
Three ways retailers can deliver meaningful 1:1 shopping experiences amidst the retail apocalypse through AI marketing
You don't have to be Amazon, Facebook or Google to turn insights into actions.
If you were paying attention, 2017 might have seemed like the year that industry pundits’ predictions about the death of retail finally came to fruition. The traditional Main Street took some major blows last year. Shopping mall mainstays like Wet Seal, Payless ShoeSource, BCBG Max Azria and Gymboree were among the casualties. Even behemoths like Toys R Us weren’t immune — in August 2017, the retail giant filed for Chapter 11 bankruptcy protection and is set to close more than 100 stores in the year ahead. The year before, victims included Aeropostale, Pacific Sunwear, Sports Authority and American Apparel.
But despite these and other signals of a big shift, retail isn’t dead; it’s just easing out of its old skin and taking a new digital form. You don’t need to be a retail insider to know that what’s largely driving this transformation is a sea change in customer expectations and behavior heralded by the combination of mobile purchasing and Amazon.com. The thrill of a visit to the mall and an armful of shopping bags has been replaced by the “Confirm Your Order” button and the promise of a box on every doorstep.
There’s no question the retail landscape is changing, but is there merit to all the doom and gloom? Amazon’s own founder, Jeff Bezos, said it best in a recent Fast Company interview: “Our customers are loyal to us right up until the second somebody offers them a better service.”
Hope isn’t lost, but business as usual will no longer cut it. Just ask Radio Shack, Aerosoles or Teavana (a few more of 2017’s casualties). The truth is that retailers who can offer a compelling, individualized experience and build lasting relationships with their customers are well-positioned to thrive in the so-called retail apocalypse.
And here’s why. The fact is, retail marketing executives have a few aces up their sleeves, whether they know it or not.
- Existing brand love: You have history with your customers. They know and love you. You’ve cultivated a brand that’s infused with meaning and identity that your customers are still willing to attach themselves to. There’s a reason Lululemon still sees more sales per square foot than any other apparel retailer (and most jewelry and electronics retailers as well) despite a price point that’s three to four times the price of alternate options. Brand love still holds sway in this new retailscape.
- Pricing trust: If a single e-commerce platform shows you 11 versions of a product from 11 different vendors at 11 shifting price points, it’s difficult to know the true sticker price. And typically on Amazon, the lowest seller wins. When a product becomes a commodity, consumers go to Amazon. But a luxury, boutique or beloved product pulls consumers to the source.
- Customer insights: Most importantly, you know your customers — how they interact with your website, your social channels, your emails and your point-of-sale. There’s no one else with the legacy of data on your current customer base. This is your trump card, and it’s the first essential step to creating a truly differentiated experience and invigorating sales.
- In-store experience: There’s a big reason Amazon purchased Whole Foods and is pioneering a transformative store experience with the recent launch of AmazonGo. Bridging the physical and digital experience is difficult, and it’s worth doing. Amazon gets it, Starbucks gets it, and BestBuy gets it. These leaders are creating great experiences across online and offline, and they are driving huge business results by making their customers happy.
Trust and love may be the foundations for future growth, but delivering meaningful individualized interactions will be the fuel to spark these long-term relationships. And you don’t have to be Amazon, Facebook or Google to make this leap.
While companies have spent millions capturing data with the promise of delivering a unified customer experience, they struggle to turn these insights into actions. The fact is, until now, it’s been nearly impossible to do true personalization, or at least to do it well. There are a few common pitfalls that lead to the often-clunky attempts at personalization that end up feeling anything but personal.
Want to avoid those pitfalls? Below are three tips for delivering relevant, 1:1 customer interactions:
- Tear down marketing silos
Seventy-five percent of consumers expect a consistent experience, wherever they engage, according to the 2016 Connected Shoppers Report from Salesforce.
Whether you call it “omnichannel,” “cross-channel” or an “integrated experience,” it’s time to create a unified customer experience. Consumers see you as a single brand, not a series of separate touch points. In that same way, engagement should feel cohesive — from the first time consumers see your email popup to the moment they step out of a physical store.
To do it, you need a complete view of your customer, which means using a centralized intelligent decisioning layer that can ingest every single one of your data sources to find correlations and optimize against. It means syncing up the digital experience and the brick-and-mortar experience — mapping the entire customer journey to design an optimal customer experience.
- Have a little empathy
If your goal is to establish a lasting, meaningful relationship with your customers — and it should be — then you need to see them and treat them as individuals. Automated campaigns have become so focused on improving immediate opens and clicks that they overlook the lifetime value metrics that are the foundation of a long-term consumer relationship, like retention and average revenue per user.
Your customers don’t think of their interaction with you in terms of a single campaign, so don’t treat your relationship as a contained exchange with a beginning, a middle and a predetermined end. Move from transactional to relational. Think beyond the next click and instead optimize for long-term human-centric KPIs, like customer lifetime value, and choose an AIM (Automatic Identification and Mobility) technology that can do it.
If you’re unable to identify at-risk customers unless they’ve abandoned their cart, contacted customer service or called out your brand on Twitter, you’re doing it wrong. Instead, AIM technologies should enable marketers to pinpoint the behavioral signal in the noise to identify and intervene early with customers who are at risk of going to your competitor.
- Never stop adapting
Amazon may have used their powerful recommendation engine to win a bigger chunk of consumer spending, but retailers now need to think way beyond simply increasing basket size. By now, most retailers have thousands of contextual behavioral data points they can use to optimize every interaction.
Your tools need to deliver more than insights—they need to be able to execute cross-channel action across hundreds of customer attributes and thousands of experience permutations. They need to bridge optimization across your site, email, social, SMS, paid media, and native applications.
Unfortunately, today’s enterprise marketing clouds primarily rely on rules-based decisioning and personalization that create human bottlenecks in your campaign process. For example, a clothing retailer might create a rule that says: if a customer of a particular segment purchases a certain pair of shoes, then deliver a message to promote this matching belt. There’s only one or two paths a customer can take. Using this method, a retailer is limited in the number of attributes and segments they can target or optimize. Beyond that, they become too labor-intensive, and so granular, they actually exclude a larger part of your customer base.
Meanwhile, recommendation engines provide incremental short-term value for the immediate transaction and can increase basket size through add-ons, but are unable to optimize customer lifetime value across channels or predict customer churn. They’re also often limited to SKU-based affinity categories and focused on linear transactional models versus optimizing across the whole customer relationship.
However, retailers using AIM technologies at the core of their marketing efforts are now able to dynamically anticipate and take action on a customer’s needs and tastes based on the full breadth of their cross-channel data footprint. While there’s no shortage of hype around AI, almost 85% of companies believe AI will allow their companies to obtain or sustain a competitive advantage, according to “Reshaping Business With Artificial Intelligence,” from MIT Sloan.
AIM technologies are finally enabling marketers to optimize for the entire customer relationship, not just short-term metrics like click-through rates or linear purchase conversions, which fosters repeat purchases and deeper brand loyalty.
And, as retailers continue to face challenges in 2018, the ability to build lasting customer relationships at scale will be the difference between surviving and thriving.
To learn more about how today’s customer-obsessed retailers are using AI to transform the brand/consumer relationship, download the full 2018 Retail AI Marketing Guide, “Retail Rising.”