How will retail change and develop in 2019? We hear from industry insiders and share their predictions for the year ahead. This ongoing series will focus on a different theme each time. Today we’re looking at one technology expected to be especially significant in the coming year - artificial intelligence (AI). As yet, a lot of what’s described as AI is machine-learning, as systems follow rules set by humans in order to speed up and scale up the processes that retailers, and others, use to do business. But in the future, the technology is set to develop further towards true AI, as systems improve to the point that they are making independent decisions.
Timothy Carey, general manager, cognitive AI at IPsoft
In 2018, as with all preceding years, we persevered through a constant stream of direct marketing emails from every vendor we’ve ever purchased from with their Black Friday and Cyber Monday deals. In 2019, expect Black Friday to be less loud and more useful as AI algorithms will take on a more prominent role in delivering personalised digital marketing at scale. With personalised emails achieving an open rate of 18.8% versus only 13.1% for those with no personalisation , there’s going to be a big shift towards AI-enabled communications delivering tailored offers based on specific customer segments and search histories. Not only will this prove more lucrative to retailers, but it will make the sales period less overwhelming for consumers.
Nikki Baird, vice president of retail innovation at Aptos
First-generation AI solutions were simple – data in, answer out. Solutions were designed to protect the average end user from confusion and distraction. While black box solutions serve their purpose, they also limit the value organisations can extrapolate by hiding AI logic, which in theory could be used to teach humans what was learned that led to various recommendations.
In 2019, we’ll see more organisations move to glass box AI, which exposes the connections that the technology makes between various data points. For instance, glass box AI not only tells you there is a new retail opportunity, it also uncovers how that opportunity was identified in the data. It also provides retailers with an opportunity to check their data – and any public or aggregate data they pull in – to ensure AI isn’t making bad assumptions under the adage “garbage in, garbage out.
This may sound more complex, because it is. Even with next-gen UX that simplifies the integration of AI into processes and workflows, retailers must invest in educating employees to make the most of these. But if we’ve learned anything in the last decade, data-driven insights aren’t a passing fad.
Sylvia Jensen, VP EMEA, marketing at cloud platform Acquia
AI and ML will prove incredible opportunities for marketers as they continue to try and improve customer experiences with their brands. However it is important that marketers understand the best use of these technologies. Consumers only become aware of technology when they see it doesn’t work and the brand they are interacting with fails to offer a personalised experience. Therefore it is important that marketers get to grips with how their martech stack works together through the buyer’s journey.
Given the wide range of AI and ML techniques available, marketers should focus on how it can solve specific challenges within the customer journey and make the overall experience better, and only deploying AI and ML where it will help them deliver the seamless experiences customers want. Adding technology for the sake of it and not doing it well is only likely to increase the gap between marketers and consumers with regards to that experience.”
There’s more on this in Acquia’s annual global report on customer experience trends in 2019.
David Nicholls, retail and hospitality CTO for Fujitsu UK
Up until now, AI has been focused on specific environments to create a dashboard on what’s happened, rather than on what’s going to happen. Retailers will begin to use AI to extract value from all forms or real-time data being collected across their operations, such as from their refrigeration systems, CCTV and control systems. Previously, this data all sat in separate silos, with retailers unable to make correlations between the data. However, through the use of AI, retailers can link the data together in real-time and create new business insights and actionable data to engage the customer, optimise stock availability and movement, drive operational efficiency, and prevent loss.
Peter Thomas, chief technology officer at shopping experience specialist Attraqt
This year we’re predicting more talk around what AI can deliver – AI and machine learning’s ability to ingest and process huge volumes of data from multiple sources, quickly – but also further confusion for retailers and brand on knowing where exactly to focus energies in AI investment.
With economic uncertainty on the increase, retailers must do everything they can to stay competitive (and survive), yet it’s getting harder than ever to engage consumers and deliver experiences that will turn them into brand loyalists. This makes AI’s promise of greater operational efficiency and its ability to deliver better online shopper experiences, extremely tempting and retailers that have bought into the technology, or are thinking of making that move, will need to learn to work smarter with it.
Embedding context, creativity and rationale in shopper experiences is where retailers will win in ecommerce. However, this is a value only a trained human merchandiser will deliver and this is where brands will need to work smarter with AI to realise its value. It is not a standalone solution that replaces a merchandiser, rather, it can offer the ability to enhance their role and unlock greater potential. Retailers will need to identify their specific strengths and weaknesses to implement AI in a way that engages with shoppers and makes commercial sense.
The technology will also force greater cross-team collaboration in efforts to eke out true value from its investment. With shared data, CMOs, IT heads and ecommerce teams will need to join forces with each other to set joint strategies and deliver real value and insight for the business.
Dan Mitchell, global director of retail and CPG at SAS
Mobile and online shopping will move toward conversational interfaces. The goal is to be able to move from keying into a search box “red cardigan sweater with buttons” to saying it verbally. Chat functions are already present in most software, and retailers will insist on making that functionality even stronger this year.
AI and IoT in retail = more analytics
From the supply chain and the distribution centre to a bricks-and-mortar store and ecommerce shopping channels, AI and IoT technologies are everywhere to make the shopping experience more satisfying. To realise the most value out of those pivotal technologies, the data generated must be analysed in as close to real time as possible. Without real-time analytics, how is your sales associate at a store on the north side of town going to know the size 12 black gabardine pants her customer needs (but she doesn’t have at her location) are sitting at a distribution centre one county over and can be shipped to the customer overnight? Inventory transparency means the sale is saved and the customer is satisfied because the retailer knows where all their inventory resides at all times.
Uwe Weiss, chief executive of AI retail solutions provider Blue Yonder
Sustainability is becoming an increasing concern: people are more worried about issues like cutting plastic waste than cutting costs, so we can expect businesses to take action in 2019. That can be easier said than done, however.
Taking the retail industry as an example, many retailers still rely on outdated replenishment tactics that are based on historic sales data, inaccurate predictions and sentiment; this approach must change if retailers are to make a real impact on waste. Retailers must take a more innovative, data-driven approach to their replenishment if they are to optimise previously manual, error-prone processes and reduce the amount of stock that is wasted, and therefore the plastic packaging that is thrown away.
While data is the door to a more sustainable world, AI holds the key. Retailers have enormous amounts of data, from past sales, customer footfall, public holidays and even changes in weather. Using Artificial Intelligence to optimise this data will empower retailers to reduce plastic waste by accurately predicting customer demand and automating replenishment decisions. Making the effort to take robust action on reducing plastic waste will not only provide brand differentiation, but also help save the planet.
Andrew Westbrook head of retail at business consultants RSM
AI will be used to learn about targets of phishing and even to replicate voice, handwriting and conversations. For those fraudsters who spend weeks or months learning everything about their target using digital information, AI will be able to do the same job much quicker. This enables phishing attacks to be more sophisticated and believable, increasing the success rate. Retailers will need to be extra vigilant when sending emails to consumers as AI fraudsters will be using your information to mimic those you trust in order to gain access to consumer bank details and more.
Atish Gude, chief strategy officer at data services business NetApp
Still at an early stage of development, AI technologies will process massive amounts of data, the majority of which will happen in public clouds.
A rapidly growing body of AI software and service tools – mostly in the cloud – will make AI development easier and easier. This will enable AI applications to deliver high performance and scalability, both on and off premises, and support multiple data access protocols and varied new data formats. Accordingly, the infrastructure supporting AI workloads will be also have to be fast, resilient, and automated. While AI will certainly become the next battleground for infrastructure vendors, most new development will be aimed at the cloud.
Darin Archer, CMO at digital commerce provider Elastic Path
Businesses are over ’AI’. The hype cycle burns faster these days and AI is experiencing a decline similar to what’s happened to the IoT. The joke going around Silicon Valley right now is that you get kicked out of a pitch if you bring up AI.
This is because AI, at the level of market perception, is unachievable by the vast majority of organisations. The challenge is that you not only need data scientists that are being hoovered up by the likes of Facebook, Google, Microsoft, etc., but you also need huge, richly codified training data and most companies are struggling just to connect their own customer data.
In addition, most of the buzz from software companies such as IBM and Salesforce amounts to nothing more than the mere evolution in natural language processing. All this means is that we are now really good at text-to-speech and speech-to-text, allowing us to create chatbots and recognise written content from interactions. What we do with that content once it’s wonderfully transcribed from voice still needs to be developed.
To caveat that though, AI is meaningful and has changed everything, including its ability to interrupt every digital record that we’ve ever created. However, it still has a long way to go to take people’s jobs - it’s unlikely AI will aid professions like marketing in a way that is accurate enough that they’ll even bother.
Considering this, I think AI is dead...or at least we’ll stop talking about it in 2019 with empty statements and start talking about business problems and business outcomes again…I hope.