metisa

Artificial Intelligence for Retail Marketing

Client

Altitude Labs

YEAR

2016

SERVICES

Product Design UIUX Web Development Data Science Machine Learning

THE CHALLENGE

Need for Data-Driven Marketing

There is a clear correlation between data-driven businesses and competitive edge. 35% of Amazon's e-commerce sales were from recommendations. Zara is giving other fashion brands a run for their money with their use of data analytics in supply chain management and sales. However, from working with marketers of several retail brands, we learnt that the way marketing is done is still very much art than science. The challenge for brands is how to convert the large amounts of customer data in the form of purchases, clicks and add-to-carts to measurable and repeatable business value.

OUR SOLUTION

ARTIFICIAL INTELLIGENCE MEETS MARKETING

Metisa solves this problem by helping retailers retain customers and boost sales with predictive emails, text messages and other marketing. The mission for us is to measure the success of how much money we make for our customers (brands and retailers) rather than focus on intangible constructs like engagement and eyeballs on each SKU. Our layer of artificial intelligence can now automate a marketer's vision and personalize it to each individual customer leaving a marketer with more time to spend on overarching long-term strategies while leaving the execution details to the Metisa engine.

First, we digitized existing processes by converting what was done with Excel sheets and emails into a cloud-based customer relationship management (CRM) system that the team could use to manage their growing database of experts, clients and projects. We ran product design and development sprints over 4 months to develop the backbone of a system that Lynk could use to store, analyze and manage operational processes.

Second, we designed and built an iOS app that could be used to gain early traction for Lynk's service for SME businesses. The app leveraged the same backbone that we had developed. Through biweekly user tests and iterations, we were able to identify core functionalities in the MVP to complete a deployment within 12 weeks.

THE RESULTS

REPEATABLE PROFIT UPLIFT

We are working with multinational companies across different industries including Zalora, Fitti, Patchun, Yue Hwa Chinese Emporium, Mischa and Klook. As our engine matures, you will not find repeatable profit uplift but uncover a world that will give you an edge to differentiate from your competitors and keep your customers engaged.

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