FMCG suppliers and retailers stand to gain significant savings in costs and time if they embrace AI across backend systems and platforms says a leading IT expert.
Eroka O’Connor had an extensive career working with FMCG brands prior to joining digital marketing solutions company Adobe, where she is a senior solution consultant for commerce. She told Inside FMCG that used in the right way, AI can be deployed to deliver much more personalised customer experiences both online and in-store by helping create more relevant and welcome communications to drive sales.
“From my experience, the main challenge that FMCG companies face now includes the need to understand customers – getting that first-party data so they can use it for their customer insights, and then using that data to drive a personalised experience across omnichannel touchpoints data,” said O’Connor.
Many businesses are already aware of – or even using – AI to create content but it has further potential in the marketing field. And adopting AI does not mean investing in complex new technologies – it is already embedded in software solutions FMCG businesses use – including tools in Adobe’s digital experience solutions such as Adobe Commerce.
“AI is not just around content creation. Think about it within every aspect of running your digital experience – not just to create content but also to remove overhead from the day-to-day management of digital experiences,” said O’Connor.
O’Connor identifies four key areas in which Adobe has been integrating AI in its tools: forecasting, predicting, automating processes and analysing behaviour.
“First comes the need to identify the right customers to target with marketing based upon their needs or their purchasing intent.”
Traditionally FMCG companies have segmented customers into groups – for example, by age group, location, or gender – all based on data they had on hand. But interpreting it has often proven to be a very manual task.
“If you can start to use AI to interpret that data to improve those segments and make them a lot more targeted and personalised, you’re going to get better sales results off that. Because we all know that personalisation drives sales,” said O’Connor.
Then, by using an AI tool to churn through that data you can identify who’s going to purchase a product, predict where and when they are going to purchase it – or if they are likely to cancel a product subscription.
“After identifying the customers, the next step is to engage them with the right message on the right channel at the right time. An AI engine can be used to suggest when you should message customers, what platform you should be sending those messages on and what message you should be sending to them.”
That leads into the next stage of deploying AI: using it to identify the most effective communications experience for customers. Is that a text message or an email? Is one subject line or website banner more effective than another? Or perhaps a push notification via a mobile app will work best. AI, she said, can help deduce which is most likely to prompt a customer to buy.
Within Adobe’s product suite is Adobe Sensei AI, its version of AI which O’Connor likens to a business’ ‘copilot’.
Sensei AI services can be deployed to accelerate end-to-end marketing workflows to improve organisational productivity and efficiency. It is already powering a number of customer experience use cases from content personalisation and editing, to marketing copy generation and conversational experiences.
O’Connor said Adobe’s AI tools are designed to integrate with existing applications used by FMCG companies in areas such as an online store’s search tool, offering customers a personalised recommendation based on previous searching, browsing or purchase history on the site and even suggesting products that can lead to incremental sales at the checkout.
“One of the problems is that as companies adapt to using AI, what ends up happening is each of the different points solutions I buy will have their own AI engine. And each of those will be using – or could be using – different algorithms. So how do I then tie all of those together to ensure that I’m giving a very consistent experience to my customer?
“By using Adobe’s Experience Cloud with Adobe Sensei as the inbuilt core AI technology as the underlying AI engine there, I can tie all of those points solutions together with one AI model running and not have to integrate multiple applications to be able to transfer my AI data from one platform to another. So my marketing and sales experience becomes seamless with less cost and less overhead which is a really big pain point for FMCG companies.”
O’Connor stresses that deploying AI is not about letting – or expecting – the technology to “make the whole world for me and make it so that I don’t have to do anything”.
“It’s all about taking the grunt out of the day-to-day work for the marketers and making it so that the marketers are adding intelligence, so they can look at the algorithms and they can look at the results that are already there.”
Adobe has also noticed how FMCG companies are working to optimise their trade spending and digitalising networks to manage their retail media presence and manage promotions.
Sales-focused forecasting, for example, involves using AI to analyse historical sales data along with market trends which allows them to predict future sales patterns: What products are going to be more popular in the future? Or to predict churn: Which of my customers are likely to drop their subscriptions and when are they likely to do so?
Furthermore, a lot of the necessary activities undertaken by merchandisers and marketers are repetitive, says O’Connor. “Why not use an AI engine to take those off them and analyse consumer behaviour?
Many FMCG companies will use an automated marketing email platform, point-of-sale solution, a content management system, possibly along with a review platform or a product recommendation module – many different features on different platforms. While some of those may already incorporate an AI feature, a disconnect can occur if the product recommendations a customer is getting served on a screen are not the same as those in an automated marketing email they receive or what a sales associate recommends to them inside a store.
That’s why integration across platforms and plugins is essential. “We use Adobe Experience Manager to do that so you’re not having to deal with that integration of your different point solutions and you’re sending the same AI recommendations or AI algorithms and their results to multiple platforms,” explained O’Connor.
Successful implementations include Catbird, a jewellery company, which saw a 17 per cent increase in their conversion rate just by introducing AI-driven product recommendations.
Another is a retailer in the US that saved 20 per cent of the time taken to develop online content by using AI to assign metadata and manage tags on online stock.
“AI is really exciting and there is so much happening in the marketplace. It’s all about sitting down and thinking about your architecture and your structure to ensure that you’re not going out and just buying the latest thing that sounds great. You need to have a firm grounding and firm architecture to deal with it,” she said.
“This is where we’re getting to, a place where marketers and merchandisers can manage these sites and do these things without needing programmers, without needing data scientists and take lumps of work off what they do day to day.”
For more information about how Adobe’s AI-embedded tools can assist your FMCG business save time and add more personalisation to your customer message, take a look at this site.
