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A large ecommerce company wanted us to build a client list based on orders through their website and use AI to help maximize sales to this list.

Step 1: We took their order history and were able to generate a 95% accurate list (name, phone number, emails, date of birth) based on shipping addresses alone.

Step 2: We used AI to categorize their customers. We were able to generate unique insights such as when certain customers buy (was it around a sale, a holiday, etc.) and what types of items they typically bought.

Step 3: Deployed AI and automation to engage with their customers intelligently based on their profile.

Result: Here was a list of shipping addresses that we turned into an extremely profitable campaign. All thanks to the power of AI.

A company approached us wanting to solve the problem of customer retention within their app.

Step 1: Look at all the user activity within the app such as login history and uses within the app. Use AI to categorize the groups of users.

Step 2: Use AI to build a predictive model, based on real time behavior, to predict when users have a high chance of cancelling their subscription.

Step 3: Use AI to automate content pushes to the user and notifications within the company to try and keep the user.

Result: Here we took simple data and were able to predict with high accuracy when someone might want to cancel their subscription. We were able to automate processes to dramatically increase the company’s odds of keeping their users.

A company who receives a high quantity of inbound leads wants to use AI to qualify these leads.

Step 1: Get the list of inbound requests. Use AI to categorize the leads based on their messaging and submissions. Categorize the leads based on their industry and other professional details.

Step 2: Use AI to Create automated replies and “funnels” to qualify the leads further and gauge interest.

Step 3: Use AI to create a feedback loop where we understood what kinds of leads were closing.

Step 4: Use AI to generate a predictive model in order to predict the percentages of closing certain leads versus others – and automate follow up/priority assignment accordingly.

Result: Here we streamlined the process of working with inbound leads, and helped the company close 12% more inbound leads.

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