A preview of 2024 trends and data challenges retail chains will face in the age of Amazon and Artificial Intelligence

As retailers celebrate the end of the holiday shopping season and anxiously plan for the new year, one subject is on everyone’s mind: data. There’s so much of it, so decision-makers must ask some hard questions in 2024. Is our data managed as a “single source of truth” for marketing and advertising decisions? Can they be utilised effectively – and ethically – for personalised marketing? How can our data work well with AI, eCommerce, or multichannel marketing?

It’s safe to say then that 2024 trends for retailers will be all about how marketing and advertising directors can leverage all that data to increase profitability.

AI, the “new” data challenge

When it comes to the topics of big data and artificial intelligence, 2023 has been a chaotic year, to say the least. Our posts in September and October covered the basics, starting with the value of data-driven retail marketing decisions. We then explored ways retail chains can use AI to enhance that value – drawing valid inferences from customer purchase behavior data. In November, we narrowed the discussion to a defined strategy for retailers, showing that AI-enhanced data can be used effectively to find meaningful “diamonds in the rough” in a mountain of data every retailer has about their products and purchase history.

AI is certainly not a new phenomenon. Ever since its early research in the 1950s – and in countless fictional stories – we have been intrigued by the notion that computers could solve massively complex problems automatically, and even autonomously. As the volume of data and sheer processing power have grown exponentially, AI has proven its worth many times over. Despite our media-fueled worries, it presents unique and powerful ways to turn our data into business success.

For retailers, the 2024 trend will be less in the generative area of AI, such as ChatGPT or Midjourney. Instead, it will be how they use AI with real-world product and purchase behavior data. As demonstrated in our recent case study, AI can enhance retail marketing effectiveness and increase overall sales.

Retail reality in the age of Amazon

Since the early 2000s, retailers have had to cope with the emergence of the eCommerce phenomenon and the rise of smart devices. This rise has meant media fragmentation, heavier demands on shoppers’ attention, and direct competition from online sites offering convenience and a sense of instant gratification. Every retailer’s nightmare includes seeing a customer browsing through the store, phone in hand, ready to price-check on Amazon. They may even make an online purchase on the spot, having used the store as Amazon’s de facto showroom.

The answer – and a significant 2024 trend – is in the wise use of multichannel marketing. This means much more than putting the same ads on every device and medium. It means that each retail brand must have a reliable, two-way connection with consumers, especially with its loyal, core customers. In today’s hybrid shopping experience, the lines between print and digital – and between in-store and remote – have been forever blurred. Targeted ads and offers on every medium are only part of the solution. Customers must also be able to find and even buy with their phones, wherever they happen to be.

This two-way, multichannel connection can only be achieved when the retailer understands and controls their data. Their vast product information management (PIM) system, their digital asset management (DAM) system, and myriad other data sources must be well integrated – as a “single source of truth,” also known as master data management. This is essential for retail campaign planning and creating effective print and digital output with regional, demographic, and personal customization. It must also provide the ability to measure a campaign’s results and, through AI, refine and apply that data to guide future campaigns.

If that seems like a tall order, retail advertising and marketing directors can take comfort in the fact that they need not start from square one. Since its founding in 1994, Comosoft’s LAGO system and the data integration teams behind it has allowed retail chains to integrate their PIM, DAM, and other data sources into a streamlined campaign planning and production process. But, like the web itself, the LAGO approach has only just begun.

The future of data marketing

Another obvious 2024 trend for retailers is that the mobile web and its constellation of AI-enabled apps are not going away. The impact on retailers and their ability to thrive in that arena will continue. But the importance of print cannot be underestimated. Even eCommerce players are discovering the intrinsic value of print in growing their business.

The LAGO system has already demonstrated its ability to unify multiple data sources, streamline the production of multiple-version print and digital output, and even use AI to optimise such campaigns. But it also has created a direct individualised marketing (DIM) system, using integrated, personalised data to create a unique customer experience throughout their shopping journey. It has also helped retailers master the complexities of hybrid shopping, providing a continuity of experience across the increasingly blurry print/digital divide.

All of this relies on detailed, expert data management and on the tools necessary to keep retailers competitive. The future of retail commerce in person or online will involve integrating existing systems with social commerce, where users can shop directly from social media platforms or whatever new thing comes with the new year.

The future of retail data technology will not be without disruption and anxiety. But with the right tools and partners, it will be a good year.

With all the media noise about “big data” and artificial intelligence (AI), it’s easy to forget that data has been at the heart of retail success since well before the digital era. Keeping accurate records of sales, inventory, and product information is as old as handwriting, while product images are at least as old as photography. Digital computing did not create information technology per se; it merely moved that information from people’s heads and pieces of paper to complex code on a device. Data have always driven retail decisions; computers made the process faster and gave marketing directors more tools to plan and deliver campaigns. However, the tools can be problematic.

Case in point: Big retailers are virtually swimming (and sometimes drowning) in the detailed product information. Nearly all of this comes from the product manufacturers. The data are often incomplete, and the product data labels or metadata are inconsistent. Retailers must refine and house all this data in a sprawling product information management or PIM system.

Add another layer of data that portrays each product in the potential buyer’s imagination. Everything must be housed in another sprawling database, digital asset management or DAM system, from product photos and videos to detailed descriptions and reviews. This setup can be plagued with the same issues as a PIM system. Things can be further complicated by the need to have separate databases for inventory, pricing, customer feedback, and sales history.

The value of data-driven decisions

Having so much data gives marketing and advertising directors a considerable advantage. It provided the means of objectively knowing all there is to know about what products they should sell more of, why (and when and where) people buy them, and how best to advertise them across multiple regions and media channels. In practice, however, it is no simple matter. Reconciling and normalizing data from different product manufacturers is a huge task. Retailers need to do this and much more continuously.

Optimizing and using data usually requires a high level of automation. New product information and images are being created constantly and must flow smoothly and accurately into their respective PIM, DAM, and other database locations. All those data sources must also “speak” with each other, providing a complete picture of each product to those planning a campaign and putting that picture into every channel output.

Think of this complex data flow for retailers and manufacturers as a symphony orchestra. There are so many different instruments and qualities to consider. It can quickly become chaotic, but they all work together under a single conductor. The “music” they create can move the audience. In the case of retail, the audience is an incredibly diverse buying public. When they respond positively to all that orchestrated data, it means measurable growth and profitability.

Realising the value of data

While most retailers and manufacturers acknowledge the value of data-driven decisions, some may need more wherewithal to make it a practical reality. Retail has become more competitive and complex, and media channels have multiplied. In response, Comosoft’s LAGO system has emerged as the preeminent “conductor” for data-driven decision-making.

LAGO is uniquely positioned to leverage that complex data and effectively channel it into various well-planned, multichannel retail campaigns. This may include Comosoft’s PIM and DAM systems but can integrate smoothly with existing PIM, DAM, and other data sources as well. As described previously and in greater detail, LAGO uses its comprehensive data framework to inform the marketing decision-maker’s planning process. LAGO can do so even when marketing decisions must be made early and before the data are complete.

LAGO’s whiteboard capabilities allow marketing and advertising decision-makers to identify ideal products for promotion, place them in the best order, and transmit their decisions directly to their design and production teams. Once a campaign has been executed, LAGO enables them to judge its effectiveness and continuously improve their decision-making process.

The benefits of integrating PIM, DAM, and other complex data are seen in LAGO’s approach to marketing campaign design. Using LAGO’s innovative plugin for Adobe InDesign, production designers can access all the related data for a particular product without spending time hunting for it. If the PIM or DAM data are updated or modified, the information or images in the layout are updated automatically. That way, the designer can focus on what they do best—design a compelling display for the campaign.

LAGO can also quickly generate multiple regional versions of each marketing or advertising piece. Once the print version(s) are created, the resulting data can be automatically channeled to the retailer’s web and mobile app channels and even used for in-store displays.

Of course, integrating and optimizing all that mission-critical data is only the beginning. Comosoft has a long history of successful systems integration and database administration—all geared to empower better, data-driven decision-making. But still, more will be required as “big data” expands. Comosoft has recently partnered with retail AI developer DecaSIM to add artificial intelligence to LAGO’s already powerful toolset. In a recent case study, a large grocery chain used the combination of LAGO and DecaSIM’s AI-based model to enhance product selection in its weekly marketing campaigns, significantly increasing per-store sales results.

There is little doubt that mastery of one’s data is the “secret sauce” for retailers’ and manufacturer’s success in an increasingly competitive world. Making the right data-driven decisions will make all the difference. As it has been with structured PIM and DAM data, LAGO promises to be a leader when it comes to using artificial intelligence and “big data” to inform those decisions.

Find out more about Comosoft LAGO and our unique approach to data-driven, multichannel marketing. Or book a demo to see for yourself.