What challenges do marketers face in implementing AI technology? | DMA

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What challenges do marketers face in implementing AI technology?


AI and machine learning tools are becoming increasingly important for many organisations. However, as the technology becomes more sophisticated, these organisations also face new challenges in terms of skills, implementation and more. In this blog, Ben O’Brien, Managing Director at Jaywing, explores more about the challenges that marketers face and how they can prepare for AI implementation, to ensure they get the most out of their marketing investments.

With customers expecting highly personalised and targeted communications, the market is more competitive than ever. This make it essential for brands to make smarter and faster marketing decisions and AI gives brands this ability. However, there are a few key challenges that marketers must consider before embarking on this journey.

Getting data AI ready

Even with the best technologies in the world available, if the data provided is inadequate, the results will not be sufficient for brands to use in predicting customer behaviour. Therefore, it is crucial to ensure sufficient and accurate data is available before implementing AI technology.

Organisations who adopt best practice data management will be those best placed to adopt AI effectively and see results. From data quality to data storage or transforming data into insight, getting data in order from the start is essential to compliantly using AI.

Team knowledge

Although AI technology is becoming increasingly sophisticated, the level of knowledge in the industry does not seem to be keeping pace. In our data-driven marketing research study, we found that 40% of companies see the lack of data skills as their biggest barrier to successful data-driven marketing within their organisation.

In addition, in a recent Infosys research study, 53% of organisations surveyed cited that developing knowledge and skills would be key to preparing for AI deployment and use internally. In addition to this, many organisations recognised the value of outside specialist help – whether to assist with planning (46%) or for knowledge gathering (40%).

As you can see, it is crucial for businesses to work effectively to ensure that their teams have sufficient knowledge of the analytics behind AI models and technology systems. Many organisations recruit outside specialists in order to help with knowledge transfer during set-up and deployment.

Getting the right AI technology

New technology, such as Jaywing’s modelling software Archetype, enables marketers to unlock much greater customer insights. These tools have the ability to create better performing models which allows brands to transform the way that their CRM campaigns work, targeting personalised campaigns and content across all channels, focused on the people most likely to respond, amending their strategies to focus retention activity, or using insights from deep within data to gain more profit than with traditional techniques. This allows organisations to focus marketing activity in the places it is likely to be the most effective.

Tools such as Archetype enable brands to model almost any outcome on almost any data set – whether it’s in pricing, product and channel propensity, customer value, marketing attribution, digital activity or a host of other fields. AI gives brands the capacity to do more, in less time, with much better results so that they can focus on what’s more important – their customers. Archetype is a significant advancement in the market and for which Jaywing has applied for a patent.

Is this a new era for AI?

The successful use of AI presents organisations with many challenges. Yet with best practice data management processes, ensuring compliance with GDPR, the right skills and external support, and crucially, the right technology, organisations will be well positioned to take advantage of the new era of AI.

For organisations to harness the benefits they need to act quickly – AI is currently a hot topic in marketing, and plenty of organisations are starting to make moves in this direction so that they can better predict conversion, re-purchasing, lapsing and more to engage with customers and prospects on a deeper, more personal level.

Find out more about Jaywing’s AI predictive modelling software Archetype and AI Consultancy Services.

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