Defining customers has become one of the marketing industries greatest hurdles. With so much data now available it is increasingly complex for brands to understand and segment their audiences. Yet it is essential they understand all the different levels of customers to ensure they truly understand who they are targeting.
There are so many channels for brands to communicate with their customers, meaning there is more data accessible than ever before. A common misconception is that businesses need something of a data genius to break it all down, but there are ways for businesses to truly understand their current and prospective customers.
With this, data management services are fast becoming the industry go-to for analysing all of this data. Its blend of interactive, descriptive and behavioural data ensures brands can gauge the different levels of customers and what they want. Such insights are incredibly important for a brand - it supports growth and ensures that customers are always the most important factor in all strategies, content and paths to purchase.
Translating into insights
Surprisingly there are few marketers who actually capitalise on the value of their own data - which should be a no brainer. 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 splintered channels.
The technologies in play are often a reason for this, often siloed across separate departments. They 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 user engagement on the site, their source and behaviour on the site to name a few.
In theory this works. However 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.
By paying an extra fee and acquiring a solution, such as Google Analytics Premium, marketers can 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). Unfortunately, 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 hindering.
With a full Google DMP (data management platform) solution that will bridge the gap 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. Ultimately it will 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.
Mobile devices usage has increased at a startling rate over the last few years, meaning that cross-channel marketing strategies have 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. It's 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.
By 2019, Google predicts that a third of searches will be initiated by voice. On top of the IoT, VR is beginning to make waves following the recent launch of PlayStation VR, alongside the growing capabilities of AI, all of which will drastically change how people consume media content and how they use different devices to do so.
The technology digital marketers can use to understand consumer trends is moving on so quickly.
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.
Using customer data to shine in 2017
With the increasing usage of machine learning and AI, data-marketing is certainly here to stay and will become a standard across the industry in the foreseeable future. This means greater emphasis will be placed on the automation of marketing activity and a greater focus pinned on data and how it is interpreted and used.
An immediate change marketers can make, 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 more progressive change 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.
A 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. Ensuring audiences are targeted through the correct channel and the correct time when they most intend on making a purchase.
Bespoke attribution modelling is one of the more advanced use cases of DMP. 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. Marketers will be able to simply provide real-time recommendations on where to invest and provide advanced forecasts on the impact of each scenario, gaining appreciation from the C-Suite and maximum ROI for brands.
It is now down to businesses to decide how much of an investment they want to make into Data Management services - the deeper they dive the further customers can be defined and turned into actionable insights. Ultimately, these are little snippets of the bigger picture, which can directly impact businesses at different times across processes, something not to be taken for granted or assumed to be too complex for marketers.
This article was first published on the Netimperative website.