A Personalised Future: Q&A with New Nosto CEO

by Hugh Williams on 18th Jun 2018 in News

It's an exciting time for e-commerce personalisation business Nosto, which has recently secured USD$17m (£12.8m) in funding and announced Jim Lofgren (pictured below) as their new CEO. Now a month into the role, RetailTechNews caught up with Lofgren, to discuss Nosto's future and the future of personalisation in retail.

RetailTechNews: Can you explain how the Nosto platform works and the technology that drives that platform?

Jim Lofgren: Our Ecommerce Intelligence Engine™ sits at the heart of the retailer’s technology stack, analysing the behaviour of every individual interacting with their store to build a deep understanding of their business and those visitors interacting with it.

Using machine-learning algorithms and statistical techniques, we’re then able to predict – and automatically deliver – the most relevant experiences in real time, wherever shoppers are, to increase customer engagement and maximise the retailer’s revenue potential. We do this across a webstore via onsite product recommendations, pop-ups, across Facebook and Instagram, and within emails.

The foundation of our engine is our Product Graph, which is a deep understanding of all the different products in your store and how they relate to each other. We capture product variant details, margin data, inventory levels, etc., and can see things like which products are most commonly bought together or what products shoppers actually go on to buy most after viewing a particular product.

How can retailers measure the effectiveness of their personalisation platforms?

To measure success, companies should focus on solving concrete challenges with clearly defined goals and be aware of pain points that can be solved by automation, rather than simply throwing technologies behind their product for the sake of leveraging the hype behind AI.

Jim Lofgren, CEO, Nosto

To enable automation in retail, the first and most important step is to focus on the data: collect the data you need, validate it, and maintain it. Utilise as many data points as possible using behavioural triggers, rather than limiting to one particular data point (such as order history, for example), and don’t silo your data into multiple disconnected sources.

It is also a good idea to approach AI and machine learning with a pragmatic approach. Follow a maturity model and focus on applying tools that influence a large share of your revenue and contain a proven ROI. Then, move into use-cases that are more marginal. In an e-commerce context, you might still make more money by showing a 10% discount coupon on a simple trigger rather than implementing predictive CLV-based targeting.

Does the effectiveness of personalisation depend on the industry the retailer is working in (e.g. groceries, fashion, etc.)? Why are there differences between industries?

While all verticals across e-commerce can leverage the benefits of personalisation, we don’t consider it to be a one-size-fits-all approach. In order for personalisation to be effective, brands should consider how this strategy aligns with the nature of their business and how consumers interact with their products in order to maximise ROI.

In the health & beauty industry, for instance, consumer decisions are more personal by nature and can drill down to the most specific preferences – texture, scent, shade, etc. So, it’s important for brands in this vertical to deliver highly relevant product recommendations across all channels and create the same intimate experience that a shopper would receive with a 1:1 consultation. While in the fashion industry brands must consider factors such as geolocation and seasonal trends to deliver the most relevant product to each individual shopper’s taste, wherever they’re browsing from.

As you move into your new role, what do you see the future holding for Nosto?

While still in the early days, I can tell you that I am incredibly excited about the future for Nosto. We are experiencing hyper growth across many of our markets. Our challenge right now is to ensure that we can service all the clients that want our solution and effectively keep up with demand.