This is how retail media networks should use AI

By Jay Kulkarni, CEO, Theorem

Global ecommerce sales are growing exponentially, buyer behaviours are shifting constantly and there are a myriad of new advanced delivery options available as retailers strive to meet the changing needs of the consumer. This coupled with the goldmine of first-party data available to retailers has led retail brands to become the highlight of the digital advertising industry by utilising their access said data to present the best opportunities for advertisers to reach customers in this changing privacy landscape.

Retail Media Networks are amongst the fastest growing industries, with gigantic profit margins and revenue streams making it a very attractive model for retail businesses to adopt. And, whilst a recent piece published by Forbes suggests that the success of Retail Media Networks (RMNs) won’t last forever, Statista predicts a RMN spend of $52bn in 2023 – it seems that many retailers are still determined to get a slice of the pie.

This model is transforming the retail industry and the customer purchasing experience alike. With the huge increase in demand and expectations from RMNs, there is fierce competition between retail brands looking to increase their market share. The path is not easy, traditional retail trade businesses must transition to behaving like media businesses if they are to succeed.

And to do this effectively they must embrace the use of AI technology.

Delivering a Unified Ad Ecosystem

One of the biggest challenges to the success of RMNs is the building of an operational framework to address the ever-evolving channel mix to deliver a true omnichannel experience. Retail Media Networks might find their tech stack, channel integrations, systems and processes fragmented. By modelling their media business counterparts by re-thinking and standardising their ad model and inventory can be challenging to navigate – but by getting the back end technology in order and bridging the gap between legacy systems, Retail Media Networks will not only achieve the most revenue from their inventory but will be able to show the true value and impact they can offer to their clients.

Such a unified ecosystem should integrate brand experience across multiple channels (website, mobile, app, email, and other digital owned properties) and deliver impactful formats that targets buyers at every point in the purchasing journey, with the correct budget allocation (weights) across the purchase funnel (awareness, consideration, purchase intent and loyalty) – and finally aligned to their client’s business goals and objectives.

The most effective way for RMNs to streamline their processes from ad serving to e-commerce delivery is to embrace the use of AI powered automation technology. Many retail brands already utilise technology platforms to support programmatic advertising – utilising algorithms and real-time bidding to purchase ad inventory across multiple channels. Retail Media Networks should also expand their inventory to allow for a programmatic approach in order to streamline the ad buying process for their clients.

However, by using automation technology themselves, RMNs can streamline a broader range of activities beyond just the buying and placement of ads. The technology allows the automation of ad creation, audience segmentation, optimisation, and reporting – massively simplifying incredibly complex workflows to reduce manual effort and enhance operational efficiency for bottom line results.

Capitalising on Real-Time Data Insights

The recent increase in data privacy regulations has undoubtedly opened a window of opportunity for Retail Media Networks to allow brands to actively target their user profiles through measurable behavioural signals – an audience centric approach that can provide relevant and targeted products in various categories efficiently.

If access to first-party data isn’t enough to attract an advertiser to use a RMN then the real-time tracking and attributing of omnichannel campaigns must be the most important driver of success – especially at a time of budgetary constraints and increased pressure to prove return on investment.

This is not just an ad-serving process but rather an end-to-end brand experience journey and a path-to-purchase and repurchase by promoting loyalty and lifetime value. Retail Media Networks can differentiate themselves in this space by again embracing AI technology to allow a consolidated platform that can utilise first-party and ad-performance data to target a consumer base and access available ad placements, whilst simultaneously offering personalised targeting capabilities, integrated channels and CRM integration.

The visibility of these real-time data insights allows RMNs to consolidate a variety of information, from the number of times an ad is shown to the number of sales achieved over the period of a campaign for example. Additionally, AI technology encompasses powerful analytics and a strong attribution mechanism that is crucial for reporting on success, performance and ROI.

The power of these AI-powered analytics combined with proper data management processes that eliminate data silos and offer enhanced optimisations and measurement will ensure that Retail Media Networks can prove their effectiveness and ability to scale.

Establish Credibility

The key to successful longevity for any business is to establish credibility in their market to promote customer retention and loyalty.  A recent piece by Bain & Company outlined elements that B2B customers valued. Unsurprisingly, products that could ease the process of conducting their business (such as saving time, reducing effort or increasing efficiency) or products that could add functional value (such as cost reduction, process improvement or scalability) were identified as important factors.

In order to gain market share as a successful RMN, a balance must be found between the demand of their advertiser clients and the relevance of the ad to the shopper. By using AI technology, RMNs have the ability to calculate ROI directly from a customer’s profile and buying preferences. This focus on enhancing the purchasing journey through a reinforced inventory placement, relevance, personalisation and an engaging customer experience coupled with standardisation in ad ops, leveraging real-time data and the ability to scale ad supply in line with client budget means that RMNs have the ability to seamlessly tie together a client’s ad spend and digital sales figures to illustrate the power of their available customer base.

Additionally, by nurturing advertiser relationships RMNs will be able to garner a deeper understanding of their customers requirements and by correlating ad exposure to sales, RMNs can exceed client credibility values to truly differentiate their offering and provide customised ad products that align to a client’s business objectives, that ensures their products are visible to their desired buyers and also provides value to the shopper by being relevant to their search.

As the competition for business in the market continues, RMNs must reposition themselves as media businesses with access to the retail trade knowledge. Those RMNs that embrace AI technology to bolster operational frameworks and automate the real time success of ad operations will be able to capitalise on the huge competitive advantage afforded by being effectively able to prove their worth.

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