As part of Solutions Review’s Premium Content Series—a collection of contributed columns written by industry experts in maturing software categories—Bernadette Nixon, the CEO of Algolia, shares some insights on the value of marketing personalization in strategies and technologies.
Back in the early nineties, Internet users were happy with the essentially static nature of the information superhighway and its passive, non-dynamic nature. However, things changed, as they always do. It started with the arrival of Dynamic D-HTML with Internet Explorer 4 in 1997. From there, we witnessed the turn of the millennium, the birth of the cloud, and the arrival of composable containerized computing.
Today’s web experiences have moved forward significantly from their static origins. Users now expect personalized, custom-aligned services that deliver what they want, how they want it, and when they want it. In an era when grandmothers know what Customer Relationship Management (CRM) means, businesses in every vertical have a pressing imperative to develop personalization functionalities.
But even in organizations that fully recognize this reality, there appears to be something holding them back from implementing the personalization tools they need. One of the reasons enterprises might struggle to blend personalization into their marketing mix often comes down to the perceived challenge involved. Even firms that understand how Artificial Intelligence (AI) and Machine Learning (ML) can help drive customer conversion and retention may feel that real-world, real-time deployment of these innovations is beyond their means.
One of the ways to get past this challenge is to implement a platform-level approach that employs the advantages of web-connected Application Programming Interface (API) technology in composable computing environments. This approach can enable a business to shift its focus beyond the quantity of the firehose of data and start looking at the quality of the information it processes.
Beyond the firehose, across the matrix.
Organizations that want to become fully digital businesses in this data-driven economy need to migrate out of their previous approach to data intelligence. The customer journey is a complex matrix of non-linear attributes that need to merge to form the backbone of decision-making in the modern world of e-commerce. This matrix combines demands and wants, trends and fashions, attitudes and environments, and previous interactions with a brand, product, or service. And now that customers are exposed to these forces across multiple devices and channels, they can capture relevant touchpoint information at a granular level. While an enterprise may operate in an adjunct position to this matrix, unless it engages with customer data across all of these channels, that data will remain siloed.
Gartner’s Christy Petty explained, “Silos must be bridged at three key points: user experience, process, and data. The experience should flow seamlessly across channels, touchpoints, and devices…and be designed across channels to meet or exceed customer expectations. Inter-silo processes should flow without interruption and again be seamless to the customer. Data must be integrated so that a single, logical customer profile is available.”
Avoid cookie-cutter point solutions.
All of this has to happen outside of the cookie-cutter point solution technologies that organizations are still using out of blind faith, a lack of next-generation e-commerce awareness, or as a result of the seemingly lower short-term cost that they associate with new solutions. The technical limitations of such technologies have a damaging effect on the way brands interact with the customer data they have captured, ultimately holding those brands back from success.
The platform-level approach is essential enough to warrant restating. A vortex of mix-and-match solutions often leads to a maelstrom of data where customer insight disappears into a black hole. As a result, enterprise search technology must leverage cross-functional tools to manage aggregated customer data, help businesses achieve a single control point, and master their marketing personalization strengths.
Failure to build personalization competencies in an organization is unfortunate, especially since most firms have a customer data foundation for strategic personalization missions. We know many C-level executives view the prospect of processing and analyzing consumer data at scale as a significant challenge, which is why failing to look for a composable, API-first approach to mastering customer data is critical.
When we say headless, we’re referring to a brand of customer personalization where the ‘head’ is the enterprise search function and its ability to find, remember, deduce and deliver the products and services that customers want. The ‘head’ sits detached from the ‘body’—the enterprise itself—and its daily operations.
Lift the lid, break the ceiling
Every successful business has a marketing function that’s itching to craft more relevant, personal, and commercially successful experiences for its customer base. The final yard to achieving this ability at scale and total capacity doesn’t have to be difficult, especially since most organizations are already part of the way there. The journey out of customer isolation and into the warm glow of personalization strategies is just a matter of using your head, even if it’s headless.