Unlocking the true potential of your data and powering your data marketing

Invest your marketing budget wisely, says Joe Peters, by making the most of your data marketing techniques.

This is the age of consumer choice: there is now a huge variety of marketing channels available and data marketing methods to engage with audiences, such as digital display, social media, mobile, video and TV, resulting in multiple touchpoints for consumers. This opens up an increasing number of opportunities for marketers to influence existing and prospective customers, but at the same time makes it harder to predict where marketing budgets can be most effectively invested.

It is no longer about reaching a mass audience on one touchpoint with one single experience.

For example, let’s take someone watching a football match. Previously, all football fans would have seen the same advertisement on their TV at half time. Nowadays, a consumer’s experience is more varied. Some consumers might be checking out Twitter, Facebook and other social networks to engage in conversations, while others are watching the match on mobile or tablet devices, or on replay services online and through TVs. Every device, app, social network and publisher presents another marketing opportunity, and with these news channels comes the capabilities to collect data about the individual consumer, traffic volumes, engagements and a variety of performance KPIs.

However, even with all of this data to tap into, it still remains a challenge for marketers to know where they will achieve optimum ROI and provide consumers with the most conducive brand experience to become a loyal customer.

Along with the existing challenges for marketers today, such as recognising and optimising to high value customers and providing insight into the impact of one channel to another, there comes a broader set of challenges thrown up by the sheer volume of data being created. How can marketers not only understand the data but also make it valuable and usable?

The volume of data available is overwhelming and not everyone has a data analyst (let alone a data scientist) on their team – yet. But campaign guesswork can be significantly reduced with the help of automated audience profiling that can find patterns within the huge amounts of data generated, both online and offline, through user interactions. Marketers can now take advantage of Artificial Intelligence (AI) powered data programmes that learn quickly and make fast real time decisions, based on quality information. If we are to really use this data effectively then we need to tear down the silos of data and allow one channel of interaction to inform the other and vice versa.

A Data Management Platform (DMP) does exactly this. It enables you to harness and maximise the value of your customer data, improve the customer journey and increase your returns with greater efficiency.

But what is a DMP?

Essentially, it is a central marketing hub that ingests data generated from all your brand’s marketing activities, your existing sales and marketing databases, data from your website, social platforms and loyalty programs. A DMP integrates all this information to better inform marketing decisions and drive the best results.

Data can also be enriched by blending in third-party data from reliable sources, such as Nielsen, Acxiom or Neustar, resulting in a comprehensive picture of your customers’ typical profiles and the best way to influence more customers of a similar nature.

So what does this look like in practice?

Knowing if a person visiting a brand’s website is an existing customer, if they have been searching contextually relevant websites, if they normally renew via the call centre, if they are following the brand on Twitter, etc, would enable the marketer to make an informed decision that leads to a conversion. The individual can be offered the option to be contacted by a call centre during their visit to the website or sent the Twitter deal again via SMS to sync up the communication, or be targeted with a relevant online ad. The DMP can also be valuable for targeting new incremental audiences. Inferred data from known authenticated users can power the way a marketer engages with anonymous un-authenticated users, this capability really increases the scale of application of a DMP and the value that can be driven.

The key focus for a DMP is to strip away the heavy lifting of data analysis and, in real time, turn big data into valuable, actionable data. Where currently there are inefficiencies around what data can be used and a siloed view from one channel to the other, marketers are now able to utilise a greater volume of their own first-party data in more meaningful ways, via a fully cross-channel methodology.

Cross-channel methodology can influence the way a marketer engages users with a brand.

For example, a user engages with a travel brand’s prospecting banner for a particular product, on arriving at the travel website they are shown content related to this product. The user leaves the website and then returns a few days later via Search, where they had been shown relevant messaging based on their previous engagement. Upon entering the travel site, the user exhibits more buying signals and registers, but still does not purchase. But the user has registered, so has moved from being an anonymous profile showing certain behaviours, to an authenticated user with relevant CRM attributes and addressable data held by the marketer. Richer audience data and additional marketing channels are now available to assist in generating an active spending client for the brand.

Marketers with large CRM data sets and a user base that authenticates across a wide variety of devices can leverage explicit data to engage with their customers across all of their devices and link together the marketing activity. It is more challenging to link anonymous users across multiple devices, but this can be done using probabilistic modelling to predict the likelihood of one user being the same user across multiple devices. This can be achieved through mapping similar behaviours such as website or in-app activity and data points such as location and internet connection point.

When leveraging AI within a DMP, the more data there is available, the more the AI will be able to learn and understand the consumer. More learnings, through a greater volume of data, results in smarter marketing decisions. Marketing teams can act on this data to integrate marketing channel activities and make them work more effectively together, as well as derive correlations that will result in informed strategies and optimal value from campaigns.

Smart messaging and eye-catching visuals are still essential to translate these correlations into actions. But with the heavy lifting done within the DMP, marketers will have more time to deep dive into who their audience is and the context of what drives buyers to engage and purchase and to make campaigns more relevant at different touchpoints.

DMPs are the place to collate and learn from data. The place where machine learning can be turned into human insights for ultimate marketing ROI. And in a world where the possibilities to engage with consumers are only increasing, it is time for marketers to utilise a DMP and unlock the true potential of their data and effectively invest marketing budget.

Read also:

Intelligent ABM: Why data is your passport to success

The power of data – data may be the new oil, but it’s only valuable if you have a reliable engine