Ed Kennedy Discusses AI in the World of eCommerce
When we inject “intelligence” into content management systems, from automating menial tasks to analyzing the tone of each piece of content, the possibilities are endless. On the retail side of things, more brands have started harnessing the technology to deliver content, increase engagement, and strengthen brand affinity. Now, B2B brands are catching on creating more innovative business cases as well. To go more in-depth on where artificial intelligence (AI) and machine learning (ML) powered technologies sit in the eCommerce world, our media reporter Laura Myers had a great conversation with Ed Kennedy, Commerce Strategist at Episerver.
More Use of Artificial Intelligence Outside Personalization
As Ed pointed out during the interview, the use of AI and ML is rapidly emerging from its initial use case; personalization. Generating personalized and scalable conversations with consumers is still essential to understanding consumer habits, context, and intent so they may better predict and provide the content, information or engagement users are seeking. In addition to this long utilized use case, this year, according to Ed, we will see more brands injecting machine learning algorithms into digital experiences with the search and product pages.
Today, I feel that many organizations are living in irony where they have too much data but know too little about what the data represents because the burden of an exponential increase in the amount of data has become the 'coup de grâce' for leveraging the power of that data. The solution is hidden in the problem, though. Given one of the premises of artificial intelligence and machine learning algorithms is handling massive amounts of data while extracting value out of it, why not gain insight through those technologies at a fraction of the cost and time without the restrictions of traditional methods and taking the guesswork out of business processes? So one of the solutions to address this irony is predictive analytics tools.
While discussing the importance of adopting predictive analytics, Ed brought up a great argument by saying that for too long, advanced analytics methods like predictive analytics had been seen an initiative that only big organizations should and could cash on, however, today any eCommerce sites should be taking advantage of those tools to get a deeper understanding of their consumers’ behaviors.
On top of this misconception that Ed highlighted, another untapped potential of AI-powered analytics that I have been noticing is how heavily marketers rely on the last-click model when they were evaluating conversions because simply, this model has been the easiest way to measure. However, there are so many drawbacks of this method as it gives credit to only consumer's last action before buying something, whereas prior touch points such as email, display impressions, generic search ads and so forth may have also led to the sale. So ignoring the prior interactions along a conversion path and only preceding the final touch before a conversion do not paint a holistic picture of consumer behavior, causing blind spots for marketers. Advanced analytics powered by artificial intelligence technology help organizations understand the full customer journey instead of being limited to referencing the last-click impact, so marketers can view a more accurate cost-benefit analysis of their advertising efforts.
Sending tone-deaf social media posts all over the place is no longer a marketing activity. At least, not a meaningful one. At the end of the day, a staggering 80% of a company’s future revenue will come from just 20% of its existing customers. With this in mind, why not prioritize the most profitable or predictable portion while you have the technology at your disposal to enable the information that you need? All you need is a great team armed with predictive insights to uncover hidden opportunities as well as competitive threats.
Commerce is Getting More Conversational
Speaking of exploring data, another rising star is conversational systems. In fact, Gartner predicts that 75% of US households will have smart speakers like Amazon Echo or Google Home by 2020. When I asked James Norwood, Executive Vice President Strategy, CMO at Episerver, about his thoughts on where we will see the most innovation in the coming months, he had said: “The commerce ecosystem is becoming more complex every day, and we think brands are starting to understand that it’s not as simple as ‘online vs. brick-and-mortar.’ There are new, disruptive channels cropping up all the time, such as conversational assistants, and to keep up, marketers and merchandisers must be agile. The ‘set-it-and-forget-it’ mentality no longer cuts it. That being said, content is still king on every channel, and the content that matters most to consumers is increasingly visual and interactive, which has given rise to a lot of conversations in the industry about visual commerce, which is definitely the next frontier, and why capabilities like user-generated content and seamless content delivery are so crucial now.”
To follow up on that conversation, Laura inquired with Ed on his thoughts on voice commerce and how eCommerce teams can best strategize their plan for 2018 with AI and new ways of interacting in mind: “Voice commerce is the interaction with a device and an eCommerce site where there is no screen to engage with. If you think about Amazon Echo or Google Home, we are getting more and more comfortable speaking to devices and performing certain tasks. I think, it will transform certain parts of ecommerce such as repetitive orders or things you have already put on to your shopping list and having them sent home or reordered,” said Ed and added: “There is still a need for traditional eCommerce experiences but the way that voice commerce will augment how we shop and provide convenience is where you are going to see a lot of growth this year. “
Conversational systems vary from bidirectional text or voice conversations (simple questions about the weather) to more complex interactions such as collecting oral testimony from crime witnesses to generate a sketch of a suspect. The backend data analysis and machine learning algorithms make up the foundation for these products. Gartner sees natural-language processing (NLP), natural-language query (NLQ) and natural language generation (NLG) for text- and voice-based interaction and narration of the most statistically important findings in the user context as key capabilities of smart data discovery. If you would like to learn more about significant business outcomes of conversational systems, some of them have been outlined here for you.
Increasing demand for personalized and contextualized experiences naturally sets a domino effect in motion of WCM vendors adopting newer technologies and trends. Therefore, artificial intelligence is no longer out of reach for smaller organizations. Episerver, for instance, has recently rolled out Episerver Insight which accesses the Episerver Profile Store that tracks and saves data about the behavior of a website visitor each time a visitor views a product, adds a product to wishlist or shopping cart, places an order and so on. To me, one of the beneficial use cases of this new addition is the ability to use actual, timely data to provide a site visitor with a custom experience as it is configured with Episerver Commerce, Episerver Perform, and Episerver Reach.
As Ed also pointed out, the use cases of artificial intelligence in the digital experience world have expanded from only providing personalized content. Today, organizations need AI-powered solutions that categorize large volumes of content and data exponentially faster than humans. For instance, using AI technologies like ML to better understand the content and what content is most important to the visitor will lead to much more accurate and productive search capabilities, and hence the ability to get the right information to the right person at the right time. Google, for example, has long championed this use case. When you make a query about a keyword on Google, as you must have noticed, the platform performs the search results based on not only that keyword but also commonly used synonyms, abbreviations or even misspellings of frequently used terms for the word.
Emerging technologies are not just limited to delivering sophisticated customer experiences as they also provide marketers with data. That way, they truly understand whether their online marketing campaigns actually lead to offline sales by measuring the relevant contribution of every single touchpoint along consumers' paths to purchase. On that note, another beneficial aspect of having an AI-powered technology in place is to receive actionable recommendations that come without bias, unlike its human counterparts.
At the end of the day, the mutual business objective should be the ability to deliver frictionless contextual experiences. One of the must-have actions that need to be taken to accomplish this mission is to create and measure new touchpoints that go beyond the web.