Getting data management right: Using data to understand your customer base

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Fragmentation – it’s one of digital marketing’s biggest hurdles. As defining customers becomes increasingly difficult, brands across the UK are looking to understand and segment their audiences recognising that it is essential for brands.

With so many channels available for businesses to speak to their audience, there is more data available on customers than ever before. But where do businesses begin when it comes to breaking down all of this data to truly understand who their current and new customer is?

Data management services are fast becoming the solution, combining interaction, descriptive and behavioural data to help brands understand what makes their customer tick. And with such valuable data comes great responsibility for marketers – they must use these insights to their advantage to not only support their business growth but ensure they are truly getting to the root of what the customer wants from their business.

Making sense of all the data

Tapping into rich data resources which hold first-party data sounds like a no brainer, but surprisingly there are few marketers who actually capitalise on the value of their own data. The reality is that many brands don’t know how to make sense of the data available on their audiences nor can they merge cross-channel data, making it difficult to create meaningful insights on how to optimise processes. This ultimately leads to a disjointed experience as well as inconsistent reports due to data coming from multiple channels.

There are many reasons for this, such as the technologies in play which are often siloed across separate departments. These include search, display, social media and more, which effectively results in fragmented insights on audiences and their behaviour. When it comes to reporting, Facebook Audiences differs from AdWords, as does Twitter from Display, so aligning data is inevitably overwhelming and incredibly difficult. And that’s not even the end of it – there is also an analytics layer of technology which reports behaviour on the site, user engagement and their source to name a few.

This is all well and good, but none of the above – apart from social media channels due to their audience-driven nature – offer more insights into who the customers are, their interests or how they spend their free time.

Of course, by paying an extra fee and acquiring a solution such as Google Analytics Premium, marketers would be able to unlock more insights on their data. As with a data management platform, they would be able to on-board customer data into custom dimensions and then build audiences that can be targeted in DoubleClick Bid Manager (DBM). However, the main issue is that Google seems to be restricting its application to the Google universe, which in today’s world of multiple marketing tech providers is somewhat limiting.

Since a full Google DMP (data management platform) solution that will bridge the gap is still not on the horizon, the most reasonable thing a marketer can do is to try to get a channel and technology agnostic DMP platform which can take audience science to the next level. This opens up new possibilities, bringing customer data from all channels to unprecedented granularity and building a fuller picture of who they are, what channels they engage with and what their demographic characteristics are. The most important aspect of this technology is that marketers can immediately act on the findings and help optimise all aspects of digital marketing campaigns on the fly.

Capturing the cross-channel experience

With increasing usage of mobile devices in the last couple of years, cross-channel marketing strategy has become the Holy Grail for many digital marketers who are trying to figure out the best way to approach this conundrum. While more than three devices per user is already complicated, it seems 2017 will bring even more complexity to the world of multiple interfaces per user reality, as its not only screens marketers need to consider, but also the growing universe of IoT devices, such as smartwatches, smart jewellery, fitness trackers and voice-controlled devices such as Amazon Echo to name a few. 

In fact, Google is predicting that in the next two years, a third of searches will be initiated by voice. On top of IoT, VR is beginning to make waves, alongside the growing capabilities of AI, all of which will drastically change how people consume media and, thus, behave on devices.

With consumer technology moving so quickly, so does the technology digital marketers can use to understand them. The data management solutions are becoming more agnostic and can pick up any signal with the ability to stitch together information from other devices based on machine learning to determine if they belong to one person or many. For example, Greenlight’s Data Management Platform allows data collection across devices and interfaces to process it all as one user ID. This has tremendous implications for ensuring that marketing efforts deliver the best possible experience for customers. Being able to identify the ownership of devices with more confidence will allow for more precise messaging, and thus more effective campaigns, leading to better CTRs, lower costs and better ROI for clients.

Making the most of customer data in 2017 and beyond

Data-driven marketing is here to stay, and will become a standard modus operandi in the foreseeable future, particularly with the increasing usage of AI and machine learning. This will result in a higher degree of automation of marketing activity, and a greater focus on data and its interpretation.

Something that can be done immediately is tagging display campaigns and extracting richer insights about users who were exposed to, for example, a video ad, to identify who the clickers are and who are the converters. DMPs will provide marketers with a wealth of information which will guide them on which additional segments are worth adding to their target audience segments in order to improve overall campaign performance. This will also provide rich, actionable insights for future campaigns.

A bit more advanced is full first-party data on boarding, which includes full tagging of client sites, all active campaigns and on boarding offline data. This allows customer insights to be unlocked on those visiting a business’ web properties, but most importantly, it could become the cornerstone of a company’s campaign planning. By identifying who the customers are before they spend any money, marketers can significantly decrease budgetary waste on the wrong audiences.

Another medium-term process that can be improved using DMP is more advanced cross-channel remarketing activity. Currently remarketing seems to be quite siloed as marketers tend to remarket to people who came through that channel, regardless of whether they came through a host of other sources such as search or Facebook, which can result in retargeting the same user multiple times through various channels.

However, by better understanding user intention and engagement on the site, brands can make remarketing more focused and effective, and retarget audiences through the right channel and at the right time when their purchase intent is the highest. 

The most advanced use case of DMP would be bespoke attribution modelling. Depending on the requirements, this means quite a bit of resource investment and fluency in DMP technology, however after mastering the campaign optimisation and audience-driven approach to digital marketing, the true value of bringing all the data into one platform can be unlocked.

One can only imagine how this can be taken to the next level with the help of AI and machine learning, which will be able to provide real-time recommendations on where to invest and provide advanced forecasts on the impact of each scenario. 

Clearly the extent to which data management services can help define customers can range according to how much of a deep dive brands want to take. Ultimately, these are the golden nuggets of information which brands often long for and which directly impact short, medium and long-term processes, so not something to be ignored. 

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