All organizations need and want to know more about their customers and prospects.
Privacy and other data hesitancy concerns are making it more challenging to get much-needed consumer data to fuel marketing and product development, optimize customer experiences, and ultimately build stronger and longer relationships.
Third-party data is becoming harder to integrate, as restrictions expand related to collection and usage. According to Forrester, organizations will increasingly engage consumers directly to gather what they have coined zero-party data (ZPD).
Forrester defines ZPD as, “data that a customer intentionally and proactively shares with a brand, which can include preference center data, purchase intentions, personal context, and how the individual wants the brand to recognize her.”
So, how do you know the right time to ask customers for information?
It starts with a map
The first step is to map the customer journey. When you can better articulate the path from initial to full engagement, you’ll better understand where additional data would help to improve the customer experience with a more custom experience. Next, applying advanced analytics, including AI and machine learning, will allow for the rapid identification of moments in the journey that are optimal to ask for and receive information.
The key is identifying the best opportunities, then serving the most relevant content to help the consumer move forward easily. Reducing journey friction is often achieved by consumers themselves providing data that can smooth the customer experience.
For instance, by simply providing purchase and delivery preferences the quality of the online shopping experience is enhanced. The more personal the information such as size, age and weight, the more value is expected in return. Predictive analytics models built and refined based on analyzing a broad range of interactions can better sync the ask with willingness to provide.
Machine learning allows organizations to rapidly scour vast amounts of consumer touchpoint data at a micro level to identify areas of opportunity. Then, algorithms that get “smarter” over time streamline customer experiences with data-derived predictions.
To increase speed and ease of use, automated machine learning (AutoML) platforms such as LityxIQ increasingly are leveraged with notable success. AutoML platforms analyze vast quantities of data and provide the tools to quickly create and refine models that seek to perfect the customer experience.
To learn more about the power of AutoML and how it can help you best engage your customers, contact us here.
