How AI is Transforming Digital Marketing Strategies to Shape Better Customer Experiences
There's no doubt that data is an essential component for marketers but how exactly do they generate actionable data and to what extent has digital transformation made this easier?
Marketers have their work cut out for them when generating actionable data, and the pandemic certainly hasn’t made it any easier, or has it?
With the dynamic between customers and companies turned on its head, adapting to the restrictions of the pandemic is vital to survival. Despite countless hurdles, the businesses that overcame the challenges are truly thriving—largely thanks to digital transformations and the adoption of artificial intelligence (AI) technology. How does this show up in marketing?
The day-to-day life of a digital marketing professional leans on some combination of a/b testing to rework logo designs or trial the effectiveness of new messaging on a web page or ad. In-depth insights on what’s working and what’s not are foundational to understanding customers and offering them a great experience. But without the right tools and technology in place, access to this data is not always easy to come by.
AI-powered technology is turning the customer experience (CX) for many organizations on its feet by championing the goal of every marketer around: understanding customer needs. Whether it's more intelligent question types, personalized recommendations, or optimizing content, here are a few of the reasons why marketers are leveraging AI.
It Provides Actionable Data
Turn the clock back a few years, and marketers felt they had to mindread to know what’s on their prospects’ minds. These days, marketers are armed with enrichment data, buyer intent data and many more signals that provide a well-rounded conversation to get potential customers to the desired product and service.
This both saves time for the marketer who knows their message and product are resonating, and it saves the customer time by getting them directly to what they set out for. We also know that potential customers have many interactions with a brand before deciding to purchase with them. It’s therefore crucial that marketers optimize each touchpoint of the customer journey to ensure conversion and long-term loyalty.
Take the example of personalized recommendations. We see this in ecommerce with ads tailored to specific profiles based on visitor or demographic data. There’s also Spotify, which crafts unique weekly playlists designed around the user’s music taste.
This subset of AI has applications in content marketing and advertising as well where it’s used to test and minimize the amount of time non-optimal content is displayed to maximize revenue. By directing a prospective buyer to relevant information, you are nurturing them on the path to the right product.
Only with this in-depth data on consumer behaviour, can you deliver an excellent experience that has them coming back. This insight on user preferences enables brands to go from strength to strength and provides the power to transform CX, fast.
It will come as no surprise that this has had a monumental impact on business success for companies like PUMA, LG Electronics, and Intuit who are shaping what’s next in the enterprise using GetFeedback by Momentive. These brands have learned the art of staying close to their customers and listening for improvements to generate a great deal of new business.
It May be Resistant to Bias
The digital revolution is well and truly underway. Since Covid-19, a number of trends have come to light alongside this rapid rise, including the need for scalable CX programs that shape great experiences for all of us, rather than restrict it for some of us. While historically this came down to accessibility among other UX considerations, there’s more to it when it comes to shaping a more inclusive future with technology.
The AI conversation can take many paths, but the stand-out companies are those continuing to build out their platforms with more predictive and enhanced capabilities that bake in diversity at the outset. Most commonly, this shows up as the subset of AI called reinforcement learning, which is arguably the closest thing we have to human thinking patterns and therefore artificial intelligence.
Yet unlike other subsets of AI that rely on predefined labeling of features within data sets, reinforcement learning has a mind of its own. It is therefore more resistant to human bias as it works off raw data to come up with patterns, some never even considered by humans.
When it comes to representing diverse voices, we also know that there's power in numbers. The more feedback there is, the easier it is to settle on a decision that resonates with all customers rather than a select few.
To put this more tangibly, a leading book publisher in the UK uses our market insights solution to run a series of character and plot diversity surveys with EMEA-based authors. The result is a pulse on how potential readers feel about the diversity represented in the leading characters (or lack thereof) before the books hit the market. This translates to a living, breathing reflection of realities, not biases.
Looking forward, AI will transform these types of pulse studies. Because the entire process is fully automated, powerful insights can be delivered in minutes, not months. While it's easy to leave out this research, the result is higher returns in the long run for having made an informed decision.
It is Built for Agility
Marketers today rely on technology that helps them to fully understand their customers and develop campaigns that meet and resolve their needs on a dime. Particularly as the migration to online channels continues, improvements to the website and mobile app experience are no longer a ‘nice to have’ but a must-have for companies.
That’s where robust technology driven by AI comes into play by empowering organisations to tackle the pandemic and their customers’ changing needs at a faster rate.
This goes beyond UI bugs or flaws in the checkout flow. Organizations are using AI to monitor metrics tied to consumer behavior and to estimate what their reward function looks like i.e. the quality-to-price ratio, what goals they are pursuing, what level of service they seek, and what features are most desirable.
In ecommerce, this might be understanding whether consumers want to save money or buy the high-end brands. Advanced CX programs detect why people prefer competitive alternatives, what behaviour users exhibit on a site, and why some are less interested in certain features like support chatbots. Once a company obtains this info, they can better understand their prospective and current customers to know who to market to and how.
Modifying and rapidly resolving user frustrations is what separates companies with repeat customers from those with buyers who run hard and fast in the other direction after their first shopping experience.
Every business is different, but investing in AI-powered technology can help them take action and automate and refine processes easier than on their own. Asking the right questions brings out the best insights that will drive improvements forward in no time.