Today’s marketers can choose from an enviable buffet of marketing channels. From print to TV, social media to in-store promotions, the ways businesses can promote their products and services is larger and more varied than ever before. However, with all these choices, there can come overload. This is not helped along by the fact that determining the value and impact of each marketing channel is more of a stab in the dark than a science.
Luckily, increasing hand-in-hand with the rise of these marketing channels is the amount of data they collect on consumers. Marketers now have an unrivalled opportunity to understand their target audience in greater detail than ever before.
Powering this opportunity is data science – a unique combination of machine learning, computer science and statistics. Each marketing channel gathers a huge amount of data on how customers interact with a campaign, and with so many disparate data sets, data science is the only way to effectively combine and analyse it all.
Using algorithms tuned to your specific marketing needs, you can gather insights on how customers engage and possibly feel about a campaign, how to increase a channel’s effectiveness, the value of each marketing channel and the best ways to influence consumer and prospect behaviour. These algorithms can also take into account the potential impact of offline advertising on customer purchasing online. For instance, the impact of a TV and radio ad campaign on web traffic can be determined.
Of course, before you begin to get insights from customer data, you need to gather it. Data from your CRM systems, paid and organic social media, digital marketing campaigns, TV and radio advertising, in-store promotions, sales, loyalty and other offline marketing can all be used to identify what convinced a customer to engage with your brand, and where.
This data can be collected through various means, and businesses hold much of it already. However, much of this data is held in different places by different departments. To get the full picture of every possible conversion point, you will need to break down the barriers between each data source, and allow data scientists access to it all. Gaining buy-in from different departments may prove tricky, but the benefits of knowing how your customers interact with your business and how to improve conversions will boost every team.
Similarly, data will differ in format and quality across each department, and time will have to be spent collating and cleaning it. At this stage, the data can also be supplemented by other data sources such as survey data.
As an interesting aside, with the rise of the Internet of Things and wearable technology, there is now even greater opportunity for marketers to understand what their audiences are feeling when in-store or engaging with offline advertising. Beacons placed along certain aisles or other touchpoints in a store can tell you what a customer has looked at, what aisles they have visited, and potentially what they are interested in but haven’t (yet) bought. Of course, knowing this, you can influence their decisions. If you already know from their other interactions that a promotion and digital marketing would be the most effective way to communicate with them, then you have the tools you need to turn their consideration into a conversion.
Further insights can be revealed if you overlay open data sources on your consumer data. You may suddenly discover that certain weather conditions make one marketing channel more effective than another. Likewise, you can see which consumers in a specific area respond better to TV advertising than their neighbouring boroughs and how this changes according to urban infrastructure and environment. Having these indications can help marketers decide what channels to prioritise in certain external conditions that are otherwise out of their control.
It has been said that with great power comes great responsibility, and the same can be said when using consumer data. Businesses have a duty to protect any personal data that they collect on their customers. This includes telling consumers exactly how their data will be used, who will have access to it, and ensuring that data is stored securely. Failing to do so will place a business at constant risk of consumer backlash in the event of a hack or other misuse of data.
Related to this is the fine line that marketers have to tread between providing personalised and timely communications to consumers, and coming across as creepy. With the ability to create highly effective and targeted marketing campaigns, marketers will need to work out where consumers’ perceived creepiness level is. Overstepping the mark can risk all your hard work going to waste as consumers abandon your brand.
Despite these warnings, it still stands true that knowing exactly what you’re spending, on what, and its ROI is an ability that all marketing teams should have. It may not be long before data science becomes the gold standard for marketing attribution. Marketers who embrace it now will become the frontrunners in the industry.
