"Do you know what my favorite part of the game is? The opportunity to play."
– Mike Singletary

This online retailer wanted to make their marketing strategy more effective, by providing personalised offers to their hundreds of thousands of clients. Artificial intelligence could do the heavy lifting, so we helped them design a real-time API that both data science and marketing teams could use.

AI is like computers were in the 70s: yes, businesses understand that it's good for something, but what exactly can it do? And either way, how much does it cost, who will be responsible for to build and run the systems? When someone mentions AI, the first thing we think of is chatbots and self-driving cars – somewhat "intelligent" machines and computer programs that have the ability to mimic human interaction. Something that you don't actually need, just have fun with.

But the building blocks for businesses are available right here and now: Google offers Tensorflow for free download, Amazon offers reasonably priced APIs for everything between fraud detection and image recognition, and many 3rd party providers are out there to enhance businesses' everyday life. The time is now to learn more and dip in.

Our client is an online retailer company with hundreds of thousands of registered customers. Such companies have tough competition as a growing number of businesses join the market. They need to keep up with the latest trends and modify their marketing strategy in order to remain relevant. Their key to success is to focus on the user. In order to improve their offer and generate more sales, companies need to understand what their users want and how they think.

Customers of our client are primarily small businesses with return purchases. With the intention to improve their business and take it to a whole new level, the client employed a data consultancy a long time ago. Their service is focused on big data analysis to advise businesses on strategies. This approach allowed them to identify segments and find conclusions such as:

  1. How many of their customers are still active?
  2. Lifetime value of the average customer
  3. How much can they spend on acquiring a new customer?
  4. Which products are the best sellers?

This information helped the marketing team to understand general habits, but this approach alone wasn't effective enough for individual customers or people who registered but never bought.

Reaching individual customers is key to increase engagement and generate more sales, the lifeline for any online retail website. Our client was intrigued by artificial intelligence tools and wanted to see what this technology can do, and whether it can help enhance their marketing efforts. The primary objective of the client was to see whether AI could discover new opportunities to boost customer engagement.

As an initial proof of concept, we've built a neural network to investigate customer habits based on email interactions. The goal was to identify patterns that emerge from newsletter and social media data: this gave us an in-depth insight into what customers are most interested in, even before they've ever made a purchase. It also allowed us to move onto the next step: we were able to cut through the noise, and build real-time APIs that work synergistically with the data analytics company's insights. These APIs can be channeled into marketing tools directly, and, eventually:

  • Improve the quality of emails by optimized marketing messages and headlines
  • Tailor promotions directly by anticipating future customer purchases
  • Keep newsletters interesting, and decrease unsubscribes
  • Perform prospect analysis across channels
  • Provide more accurate pricing and inventory insights, using learn and adapt insights

Thanks to these newly-implemented changes, the improved their marketing strategy which already led to greater customer engagement and, in the end of the day: more sales.

We don't share names in these case studies – while we are proud of our clients and their stories, we respect their privacy and business. For references, please get in touch with us directly.

What we do

Digital project rescue

Project failure statistics are sobering. Big and large, almost one third of all digital projects are realised over budget, over time, or not at all – leaving jobs and businesses at risk. We are experienced in stepping into digital projects at the 11th hour, to get technology back on track.

Technical due diligence

With 100 million new businesses created and 70 million shut down worldwide each year, buying and selling startups and their technology is common practice.
That doesn't make it any risk-free.

Data analytics & research

The real big data challenge is only human. We have to learn to ask the right questions, recognise patterns, make informed assumptions and predictions. Understanding what technology can and cannot offer is step number one.

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