There’s a reason the global consumer experience management market is now worth more than $11 billion and growing: Just when we think we’ve hit the ceiling on expectations, consumers raise the bar once again. Today, every exchange between a consumer and your business — whether they’re browsing your online store, engaging a chatbot, or skimming your Instagram page — has the potential to make (or break) the relationship.
Consumers demand a seamless, personalized experience that’s consistent across the entire journey, and they’re not afraid to abandon all notions of consumer loyalty if you can’t deliver. According to recent data from Zendesk, 61% of consumers would switch brands after one bad experience. Of those who might give brands another chance, 76% won’t give them a third chance.
If you’ve been in the consumer experience game for a while now, this information shouldn’t surprise you. What might be more of a head-scratcher, however, is how fickle the pandemic has made them. Roughly 18 months into the pandemic, McKinsey & Company found that approximately three-quarters of consumers had tried a new store, product, or shopping method, and more than 80% said they had no plans to stop that behavior.
With consumers more willing than ever to defect to one of your competitors, you need to zero in on delivering digital personalization at scale if you want to compete.
Achieving Digital Personalization at Scale
Personalization is key to curating an excellent consumer experience. Brands that can create one-to-one connections with their target audiences through tailored offerings and outreach tend to carry more favor with consumers (71% of whom expect personalization, according to McKinsey). In turn, they tend to perform better financially. In the ultra-competitive business landscape, meeting heightened expectations for personalization is tough. Without the right tools, however, it’s downright impossible.
For personalization to be effective, it must be scalable. To ensure scalability, you need the help of data science and artificial intelligence. Only then will you achieve digital personalization at scale. To that end, here are four steps to help you get started on your predictive personalization journey:
1. Adopt a consumer-centric approach to goal setting.
More than half of brands plan to level up their consumer experiences over the next year, according to Zendesk. To ensure your resources aren’t wasted, set business goals that are specific, measurable, and consumer-centric. For example, focusing on improving sales is too broad. Plus, it’s not centered on meeting and exceeding consumer expectations. Instead, a more consumer centric goal might be to increase checkouts by 25% with personalized product recommendations, which will not only provide more value to consumers, but also increase sales.
2. Use data to understand consumers on a deeper level.
Refining the consumer experience starts with understanding consumers’ wants, needs, and preferences. And according to Zendesk, more than 76% of consumers expect personalization using data. Luckily, brands today have more data available to them than ever — they just need to use it effectively to make decisions. So, set a foundation of data science within your organization to really understand how to improve the consumer experience.
3. Integrate AI-powered solutions.
Leveraging data science is a significant hurdle for most brands, but AI solutions can bridge the gap between non-technical marketing teams and data-driven marketing. Marketers are only human, so there’s a limit to the amount of data they can analyze. AI can find patterns in data that humans simply cannot, thus helps capture opportunities that otherwise might be missed. For example, your consumers might celebrate different holidays throughout the year, like Diwali, Chinese New Year, etc. AI helps analyze purchase trends and offers relevant recommendations based on individual consumer preferences, and also accounts for contextual factors like location. Consumers will get recommendations based on where they are located, as well as the holiday they celebrate. So even though me and my friend both live in Toronto, Canada - I would get timely recommendations for Diwali and Boxing Day sales and she might get recommendations for Christmas, Boxing Day, and Chinese New Year based on her spending habits. Instead of marketers spending countless hours on a Christmas or New Year's campaign, AI enables brands to capture all opportunities and provide consumers exactly what they are looking for. And with 70% of consumer interactions set to involve an emerging technology this year, the time to embrace AI in digital marketing was yesterday.
4. Partner with the right vendor.
Not all brands are equipped to implement personalization at scale on their own — assembling an in-house data science department isn’t exactly easy or cheap. However, not all vendors are created equal, so make sure you know what you need in a partner. For example, although AI is an effective capability across industries, you need to make sure that it aligns with your needs as a company. You need algorithms that are built for your industry and a vendor that understands your business to see ROI and get results quickly.
Today, predictive personalization has become table stakes in the world of consumer experiences. Brands that can get it right will enjoy higher conversion rates, increased sales, and more consumer loyalty. Every organization is capable of enabling predictive personalization at scale by investing in the right technology, adopting a data-driven mindset, and working with the right vendor.