Digital transformation in retail: A Q&A with Nosto
Driven by the growing importance that both new and traditional firms are placing on technology, the retail industry is arguably the most competitive it has ever been,
Speaking to Jim Lofgren, CEO of ecommerce specialist Nosto, we gain exclusive insight into how retailers are looking to implement new services and technologies as consumers continue to heightening their expectations across the industry.
1) What attracted you to working at Nosto?
Nosto operates in the most interesting and innovative industry - Artificial Intelligence - which will impact the majority of the world’s population in the coming years in ways we are only beginning to imagine. The company’s foundation is fantastic, as it has in only a few years become one of the fastest growing and most successful AI businesses in the online retail segment, which also fits perfectly with my background as both an online retailer and system provider.
2) How will your time as CEO of North America at Klarna aid you in your new position?
At Klarna, I had the fortune to help the company achieve incredible growth across all markets, including Europe and United States, between 2015 and 2018 as VP & GM of Klarna’s Global Accounts business. In 2017, I was made CEO of Klarna’s North American business, and together with a talented team executed changes in the Go-to-Market strategy which enabled a significant transformational shift in the North American business with record number of merchants signed up in 2017. The experience I bring into Nosto obviously builds on this experience, as well my background from Enterprise and SMB sales as GM at CommerceHub, and almost 10 years as VP or CEO of US and European online retail businesses such as Ellos, La Redoute and Fullbeauty.com.
3) What are the key motivations and goals at Nosto?
Nosto’s patented technology and machine learnings capabilities for online retail is unparalleled, and is offered to merchants with the lowest level of effort made available in the market today. The product and engineering teams at Nosto is regarded as the most innovative in the predictive technology segment for online retail software, and its staff across locations such as New York, Los Angeles, London, Berlin, Stockholm and Paris carries the an incredible amount of respect in the marketplace. I am hugely excited about how Nosto will transform the customer experience with its 1-1 marketing capabilities and unbeatable predictive recommendations across all the customers touch points.
See also:
4) How has ecommerce changed over the course of the past decade?
The internet has quickly evolved into the go-to medium for marketing and advertising of products and services, which has made ecommerce a key focus for retailers worldwide. With a tremendous growth in the number of online marketplaces, brands and consumers alike are capitalizing on the ease and instant gratification that online retail provides. As ecommerce becomes more sophisticated over time, consumers now anticipate fluid shopping experiences across multiple touchpoints and channels - mobile being one channel in particular where retailers can connect with consumers beyond a brick and mortar experience. Personalization is a key player in this evolution: brands now have the ability to leverage behavioral data to offer completely tailored experiences across their site, via social advertising and email, and recommend products to consumers based on factors such as personal affinities, geo-location and shopping patterns. This empowers brands to deliver the same 1:1 experience that their customers would receive in a traditional brick and mortar store.
5) Have retailers had to adapt as the demands and expectations of consumers have changed?
Absolutely. Now more than ever, consumers expect to receive the same 1:1 shopping experience online that they would receive in a traditional brick and mortar store. And not only are they expected to deliver that level of personalization online, but they also have to do so across multiple touchpoints and channels. One area of focus for online retailers has been improving the mobile shopping experience, as consumers are now shifting towards a more mobile focus due to easier accessibility.
6) What advantages do startups have over traditional brick and mortar retailers?
Online retail enables consumers to shop via numerous platforms and channels - anywhere, at any time. And with the ability to easily track logistics and measure product performance, brands can plan and maintain product stock more strategically. The personalization factor is a huge one, as brands are able to leverage consumer data to deliver tailored product recommendations across various channels. This, coupled with the freedom to browse and purchase products at their leisure, makes online retail the preferred medium for shoppers worldwide.
7) How crucial has technology transformation become to ensuring success across ecommerce operations?
The consumer shift towards mobile shopping has significantly impacted the level of success for online retailers, as they now have to optimize the user experience on smartphones to deliver the same quality service. Technology advances have also made personalization a standard component of the retail journey - which means that a standard automated service won’t do the trick. Retailers must now focus on servicing customers via social sites like Facebook and Instagram, and across relevant areas of their website (on various platforms) to drive higher revenue for their ecommerce business.
8) What are the most common challenges that retailers are facing in their digital transformation strategies?
While huge amounts of valuable data are gathered on every customers interacting with an online store, leveraging that data to impact the customer experience and grow the business is not easy.
One challenge is that customers interact with a brand at different touchpoints. They may first come across their business on Facebook and then receive an email on their mobile and then, a week later, visit the site on a desktop computer with the possibility of buying something. As a retailer, how do you tie all of that data together in a meaningful way to ensure that a consumer actually goes on to purchase something?
Data is also typically locked away in silos. As online retail becomes more sophisticated, ecommerce professionals are adding more and more tools to their ecommerce tech stack. While this is great in theory, trying to get these tools to talk to one another is difficult. In most cases, retailers don’t bother to. The result is that you have really valuable data on their customers locked away in one tool that never gets shared with another - which is a huge opportunity cost.
Finally, even if retailers are able to pull all this data together in some unified format, how do they actually go onto action that data to improve the customer experience and drive more value?
A lot of companies attempt to solve these problems using CRM-based customer segmentation tools to deliver some level of personalization. The problem with this is that these only look at transactional data - which we’ve seen from our research is typically less than 2% of the data generated by shoppers, so they’re ignoring a huge amount of valuable signals captured in that 98% of data. It’s just not a scalable strategy.
9) How important has artificial intelligence become to the industry?
AI is the buzzword du jour in the online retail industry; but while companies are quick to leverage the hype surrounding it, the reality is that AI is a technology that is revolutionizing the way brands interact with consumers. One challenge is identifying companies who actually use AI to automate and improve their products versus those who claim to use this technology, but in reality offer more basic programs. Challenges considered, the understanding of AI continues to evolve in the retail industry. Over time retailers are learning that, rather than focusing on AI, they should focus on how to best manage their data via Machine Learning techniques. Since there is an incredible amount of competition and opportunities for quick monetization, the retail industry is a great proving ground for new technologies such as AI and Machine Learning.
10) What are some of the key ways that AI and machine learning are being used to enhance online shopping experiences?
One of the most prominent developments in Machine Learning is deep learning, or neural networks. This approach attempts to replicate how neurons in the brain work, which requires a significant amount of data. What is often ignored is that many applications - especially in ecommerce - also require the use of shallow learning. This is necessary since a product might be in stock for a limited time, or a customer engagement onsite might be limited to just a few clicks - but as an online retailer you still want to deliver personalized and relevant experiences despite the limited data.
Nosto, as well as other industry players, are striving towards ‘ecommerce singularity’: The perfect state where a shopper's needs, desires, context and budgetary and technological constraints are understood and aligned perfectly. We aim to provide a unified personalization platform where data flows through multiple sources, into one coherent service. That data is processed using proprietary technology, creating rich relationships and profiles for products, individual users, segments and micro-segments. These relationships and profiles can then be targeted, configured and filtered through our innovative interface to coordinate a seamless omnichannel personalization experience onsite, offsite and via product catalogs. This leads to increased usability for the end-user.
11) What predictions can you make about technology in the ecommerce market moving forward?
We envision personalization as a marketplace facilitator: using deep learning to identify similarities in stores, allowing us to map all catalogs into one “master catalog.” This would essentially enable retailers to map knowledge from one merchant to another. In addition, evolutions in personalization may enable it to become an agent of both the customer and the brand. For customers, this would require differentiating between “need” and “want” products, using Machine Learning to push the customer through a sales funnel while understanding the complex motivational system of the individual. It would require indexing more contextual lifestyle data points, such as understanding a person’s event schedule, moods, varying purchase intents and then going out and finding the right product anywhere on the web based on that. If the intent is understood perfectly, this could strengthen conversion rates incredibly.
Brand-wise, personalization solutions have the potential to become an integral part of the buying and inventory optimization process. Ideally, a product would be engineered, personalized and created/purchased on the fly if purchase intent is detected. This approach would be 10x that of dropshipping - an already huge business in retail today.
