Why are retailers investing big dollars into AI technology?
Because AI applications have the potential to forever change all aspects of retail–including loyalty programs.
AI applications can help retailers meet consumer demand for personalised offers and deliver them efficiently at scale.
There are, however, a lot of unanswered questions. One of those is, when will this technology be ready for implementation?
AI Adoption Rate Expected to Surge
According to one study, AI adoption in retail is expected to surpass 80 per cent in the next three years. Additionally, predictive and prescriptive analysis investments are expected to double over the same period of time.
While the rate of change is still impressive, what’s holding retailers back from adopting AI quicker?
This surge in AI integration presents an opportunity for retailers to rethink their loyalty strategies. By harnessing AI, brands can move beyond a one-size-fits-all approach and create dynamic loyalty programs that adapt to changing consumer preferences in real time.
Retail marketing strategies remain fundamentally unchanged, blending traditional and digital approaches. Digital advertising spending is growing rapidly, but traditional marketing isn’t obsolete either; it’s evolving.
Customers are often looking at a product in store but then buying it online, they also now expect more personalisation in their shopping experiences, both digitally and in-store. So, it’s important for retailers to adapt to meet customers’ digital expectations while recognising that in-store experiences are still crucial.
The trend is towards a seamless omnichannel experience, integrating both physical and digital elements. AI is playing a role in reimagining these strategies, as companies explore its potential in retail marketing.
Predictive AI Versus Generative AI in Loyalty Programs
The role of AI in business and society is still finding its place. Since the emergence of ChatGPT in 2022, the world’s eyes have been transfixed by generative AI without fully understanding how it will be applied or where it should be positioned.
One distinction to make is the difference between generative AI and predictive AI. Retailers using generative AI adopt the technology to create original content, like patterns, images, and text. Generative AI engines rely on existing data patterns to create something new.
In contrast, predictive AI uses patterns in historical data to project future outcomes. In other words, it can support strategy formulation and decision-making. Retailers already make data-driven decisions, but predictive AI’s emergence can take it to the next level.
With predictive AI poised to be a major gamechanger for retailers, we think there are three key points retailers should understand about AI adoption within a loyalty context:
- Data quality is imperative
Predictive AI is an exciting development in retail, but it remains in its early stages. Just as future customer behaviour cannot be predicted from a single data point, usable retail AI outputs (like measuring a shopper’s brand affinity) need sufficient data to be effective. Similarly, AI models trained on poor-quality data will generate subpar outputs. Therefore, pre-processing data, from that perspective, is of paramount importance.
- Optimal integration of AI outputs:
When implementing an AI model’s outputs, there is a trade-off between full automation (AI outputs trigger events such as emails, promotion offers sent to clients, generated images used for real-time ads, etc.) and systematic manual review.
Sometimes, the choice is obvious. However, finding the right implementation balance often requires adapting existing tools (or using purpose-built monitoring dashboards), putting common-sense guardrails in place, and enforcing manual review when AI predictions are uncertain.
- AI system optimisation:
A significant driver of the relevance of AI outputs (prediction/content) is the ability to
see whether predictions are correct or not. This allows for the next round of AI system optimisation, driving the performance upwards. This continuous improvement cycle can end up being a solid competitive advantage.
The first step of the journey to AI integration might seem high, but retailers should understand that optimisations multiply quickly, and the initial performance improvements are only the beginning.
None of these limitations reduce the value of predictive and generative AI, but brands must be aware of them when integrating AI into various retail marketing niches, including when planning sales, promotions, and loyalty program alterations.
What’s Next?
The landscape of loyalty programs is ripe for transformation. By leveraging AI, retailers can create loyalty strategies that not only meet but exceed customer expectations. As the journey to integrate AI into loyalty programs begins, retailers should recognise the initial challenges as stepping stones toward creating a dynamic, future-ready loyalty framework.
To explore more about leveraging AI for loyalty programs and retail marketing, check out our comprehensive whitepaper, Eagle Eye’s AI Anthology. It’s packed with insights and data from our AI experts to guide you through the evolving retail landscape. Click here to read more.
