Top data strategies for winning retail marketing campaigns

By Michele Iozzo, Managing Director Middle East & Africa, Criteo

By Michele Iozzo, Managing Director Middle East & Africa, Criteo


Personalisation is the most powerful way for ads to stand out, especially in the noisy digital world of today. Most marketers know that brands that have been unable to successfully incorporate data into their marketing campaigns have failed to generate eyeballs.

This means that data needs to sit at the heart of everything a brand does. According to 2018 Winterberry and IAB survey, just over 1 per cent of respondents were confident that their organisations have the right expertise, experience and skills to get the most value out of their data. A majority felt that data analytics was one of the most important skills required to create a successful campaign.

A recent survey by PwC in the region seemed to mirror this view. It found that CEOs in the retail sector are on a massive digitalisation drive to address changing consumer habits. The Dubai Chamber of Commerce and Industry also found that Dubai’s retail sector will continue to grow at a compounded annual growth rate of 5.2 per cent over the next five years. This demand will be fuelled by visitor spending, mega international events like Dubai Expo 2020 and booming e-commerce.

This growing volume of shoppers who browse for products, watch videos or generally surf the web will leave a trail of digital data. These patterns and behaviours reveal valuable insights that can be used to predict needs and develop informed marketing strategies.

But many brands aren’t using data correctly or don’t know which kind of data is most relevant. In fact, many retailers simply don’t have the data volumes to deliver truly shopper-centric strategies. But, armed with information on shopping history, social media habits, and even geo-location, retailers can personalise experiences better than ever before. The data must be processed and interpreted intelligently to deliver real-world results, both online and offline.

This information can be used to generate content that actually matters to the consumer when it matters most. The businesses that are able to achieve this complete view of their shopper will survive and thrive in this new world.

But achieving these results isn’t easy. Brands, retailers and agencies alike are very often at loggerheads when it comes to what information belongs to who, and how it can be shared. But they do recognise the data opportunity and are collecting and analysing it as quickly as they possibly can.

This could mean retailers sharing real-time POS (point of sale) and inventory data with brands, giving both companies access to system insights to better plan for promotions and operational efficiency. In isolation, there are significant data gaps, leaving an incomplete picture of their customers and delivering a stunted experience as a result.

Fortunately, there is a conscious realisation among businesses that their collective data sets are stronger than the sum of their parts. The conversation between parties involved has become more common in recent times as they look to overcome challenges around data sovereignty and gaps in technology. This approach is enabling them all to respond to rapidly shifting consumer behaviour through cooperation.

The power of data doesn’t end at delivery. The use of information is essential to evaluating the success of modern marketing campaigns. Many brands have discovered that traditional evaluation metrics including ROI have been short-term in their scope and reinforcing of negative trends.

Today, a thorough analysis of data in the evaluation phase of a campaign can ensure that marketers are taking a more strategic approach to campaign measurement. Customer lifetime value (CLV) is the total value a consumer brings to a company throughout their lifetime. CLV is calculated by adding up the revenue earned from a customer over their lifetime and then subtracting the initial cost of acquiring them. Despite certain challenges, CLV is a huge opportunity for businesses to enhance the quality of the service it provides to customers, and making the best use of available data can facilitate this.

Machine learning and artificial intelligence (AI) are also helping to ensure experiences are customised for every shopper, at a volume and speed no human can beat.

Using AI, retailers can create models to help understand customers’ desires, motivations and actions across both physical and digital channels. Decision-makers are well aware of this potential; a recent IBM study of more than 1,900 retail and consumer product leaders forecasts that the adoption of intelligent automation in the retail space will rise from 40 per cent of companies today to more than 80 per cent in three years. AI can also help retailers to make better strategic decisions on the future of their business, including optimising existing store space and locations and predicting future store performance when expanding their physical footprints.

The brands that are successful in their data strategies will be the ones who win out in the long run and successfully navigate the tough times being witnessed across the marketing world right now.