Retail - more relevant personalisations

Flavio's food and drinks business is growing. He's getting new Customers, and building up a base. He has various sources of data, e.g. orders, ecommerce, digital events and email channel data. He feels that there's a wealth of untapped insight that he'd like to harness, so that he can devise some sort of strategy for both outbound and inbound communications. But he doesn't know how or where to start...

nudgeML™ can bring together the various silos of data, allowing Flavio to understand his base, see where he can cross-sell, upsell, and retain, and then link personalised 121 content into the website for display in the appropriate pages.

nudgeML also allows him to proactively reach out to his Customers via outbound communications, by passing the hot leads associated with each Customer. This ensures that each touchpoint can be tailored for each Customer's contextual needs.

Estate Agents - recommending the right property

OpenSpace Properties wants to get a better hit rate with its property recommendations. Currently, it's simply filtering properties based on the Customer preferences, e.g. max price, number of bedrooms. Sumhar has suggested that recommendations could be improved with modelling the Customer and property characteristics, to determine optimal fits...

nudgeML allows for rapid Customer data feature creation, given a rich set of underlying data. It combines this with the property data to provide recommendations with a better hit rate (sold vs not sold). This results in more frequent sales and happier Customers.

Harnessing Paid Media

Charlie's growth targets include retention and acquisition. Her Customer marketing engagement figures are declining which exacerbates the challenge, plus she knows she ought to be reaching out to paid media channels for acquisition purposes as a minimum...

nudgeML allows Charlie to create and combine Customer value and churn risk details to target retention and acquisition strategies. For example, she can target the top high value/high churn/disengaged Customers via paid media, as well as collate high value/low churn/engaged Customers for look-a-like acquisition matching. She is also able to configure channel outputs such that the right data and format is made available for the social media platforms of choice. Finally, after creating and delivering the targeting data, Charlie can track the success of the retention and acquisition missions within the tool.

Tell us about your Challenges

Although Use Cases provide confidence that nudgeML can potentially help you, your challenges will ultimately be unique to you.

Please do get in touch if you'd like to talk through your challenges and want a steer on the options available to you. nudgeML could work for you, but there may be alternative approaches that we can suggest for you.