ShopFluency is a “personas” company that helps you create detailed personas of your customers. They provide data-enrichment that helps you identify your best customers, and find more detailed data points about those customers, thus enabling you to create better lookalike audiences with that data.
ShopFluency appends first-party customer and household data (from data centers like Experian) onto consumer database information in order to help brands understand where your best customers are coming from. Then they feed that into their Machine Learning model which breaks up these customers into multiple persona’s/demographics. Once you’ve identified these different personas, you’ll be able to focus on your higher Return on Ad Spend (ROAS) customers, and you can adjust messaging to those segments and improve conversion rate.
Personas can improve your targeting and messaging dramatically, decreasing your cost per acquisition by up to 30%.
ShopFluency helps brands create personas across product categories, across value, across geography, and across time - as the audience profile or product lines change.
Once your data is enriched, ShopFluency can push it to Facebook, Google, your email service provider, or your data warehouse/business intelligence platform for you to use across multiple campaigns.
What’s a Rich Text element?
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
Static and dynamic content editing
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
How to customize formatting for each rich text
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.