3 Challenges to Improving Personalized Experiences and Engagement

A recent roundtable event brought together leaders from across retail and CPG to discuss the state of personalization in advertising and upcoming challenges as the marketing landscape continues to evolve.

The rapid acceleration of digitalization has increased both consumer demand for personalization and the complexities of achieving it. However, advances in technology and innovation can empower savvy brands and marketers to improve personalized experiences and engagement.

As I participated in the roundtable, I noticed three key challenges emerging as well as ideas on how they might be addressed moving forward.

Discover actionable insights amid a deluge of new data

The rapid rise in ecommerce and the acceleration of retail digitization has not only caused new consumer behaviors and trends; it’s also resulted in an eruption of data. The ability to leverage this data can be an essential competitive differentiator, teaching us how consumer thoughts and behaviors are changing from one moment to the next as well as informing how, when and if marketers should approach engagement.

But effectively interpreting and responding to this data can be costly and challenging. As Scott Lux, SVP of customer experience at NOWwith, discussed, it’s often difficult to determine what to pursue. Which consumer trends are here to stay, and which will be outdated before a campaign can be launched? How can retailers and CPG brands efficiently isolate valuable data from noise and transform those signals into actionable insights?

AI advertising enables marketers to rapidly process huge amounts of data, helping them understand and respond to the right signals instead of wasting time and resources on making guesses and chasing trends. For example, IBM Watson Advertising’s Weather Targeting solution uses AI to anticipate how weather will impact when consumers are likely to shop, what channels they’ll use and the products they are likely to purchase.

These capabilities help marketers influence retail behaviors and product demand at a local level through data-activated and informed media. In fact, we’ve seen this technology increase in-store foot traffic by nearly 200% and purchase intent by 20%.

Deliver personalized experiences without sacrificing scalability

Personalization was a primary topic of the event. There is an apparent paradox in the idea of delivering unique experiences at a scale that makes the campaign cost efficient. The danger of hyper-segmentation is that marketers can get so specific with the targeting that—while the messages can be effective—the scalability is lost.

AI advertising enables marketers to rapidly process huge amounts of data, helping them understand and respond to the right signals.

Mara Greenwald, managing director of commerce and performance media at Mindshare, described this as the next big challenge: How do marketers make personalization scalable without thinking about audiences too singularly?

Recent advancements in AI create the possibility of privacy-forward solutions that treat each consumer as an individual while delivering exceptional marketing experiences, effective outreach and measurable impact at scale. These solutions can support direct engagement and personalized conversations with a wide base of consumers to help build stronger relationships and unearth valuable insights for future strategies.

As a leader in the do-it-yourself market, Behr launched an IBM Watson Advertising Conversations campaign to reach consumers with personalized recommendations for choosing paint colors and starting their project. The campaign drove over 10,000 1:1 interactions with consumers, with interactions that were more than three times longer than Google Rich Media interactions.

Predict consumer reactions before they happen

You don’t get a second chance to make a first impression, which is why the roundtable also spent time discussing the need to effectively anticipate which creative experiences will surprise and delight consumers across devices and interaction points. Further, brands must understand who and when to engage, as well as identify the best message medium and elements. Doing so means more than responding to consumer behaviors in real time; it’s about being ahead of those reactions.

This is easier imagined than accomplished, especially with the loss of cookies and private data. But applying the right technologies to privacy-forward datasets such as weather and location can help this level of anticipation become a reality, predicting the timing, platform, product, image, video, messaging and offer that will deliver an effective personalized experience.

IBM Watson Advertising Accelerator technology is designed to identify the best performing display and video creative variants to serve each individual or household, optimize against secondary consumer actions like conversion rates and gain valuable insights that empower teams to quickly pivot based on consumer needs. A national retailer applied this technology to its library of creative elements and assembled hundreds of different audience-specific ads. Variations were based not only on how consumers were reacting, but also on other key signals such as designated market area (DMA), device type, weather and time of day.

These efforts enabled the brand to increase performance by 200% by segmenting millions of customers into 20 performance groups and serving personalized messages that anticipated which experiences would resonate best with each group.

The future is now

Market expectations are growing in terms of personalized engagement and experiences. The potential benefits of meeting these demands are clear—improve effectiveness, engagement and efficiency. As consumer behaviors and loyalties remain in flux from the effects of the pandemic, the retailers and brands that are savvy enough to adopt new data-driven strategies will likely see immediate growth and rewards that could carry them far into the future.