Do marketers need to be data scientists: Exploring personalisation, programmatic and big data
Picture source: innovation.internews.org
The proliferation of digital and social marketing channel provide an explosion of customer data. CMOs must face the challenges of analysing this data, using it to personalise communications and fully capitalising on the opportunities provided. In this guest posts, Sean Jackson, Chief Marketing Officer at EXASOL explores the data insights that make a difference to marketers.
On October 24 1994 the banner ad was born. Wired Magazine’s predecessor, Hotwired.com came into being and hosted a banner ad produced by AT&T. You can still see the advert at thefirstbannerad.com. Turning to the present day, with smart devices infiltrating ever corner of our lives, big data has come of age.
What does this mean for marketing?
Customer centricity, personalisation, and really understanding your customer are all good ingredients for marketing success. Big data makes this achievable, especially as we move into the age of the Internet of Things. Soon, every device we own will have the capability to collect data. This can be mined for valuable insights into individual customers.
For marketers, it makes response rates trackable in real-time, bringing marketing accountability and clear economic indicators as to the success of a campaign. Now is the time for marketers to start using the technology available to really make a tangible impact and look great in front of the business.
Data insights can make a difference to marketing – it’s not just hype
Data-driven solutions can result in highly accurate insights into customer behaviour on desktop, mobile devices and social media. This is not ground-breaking news to marketers’ ears but the key is in the brand being able to properly analyse this data and use it to engage users in real-time, thus improving marketing activity and ROI.
In today’s digital marketplace, having accurate data analytics can make or break a company
Take programmatic ad solutions provider myThings for example. Through ‘dynamic personalised retargeting’, brands can engage users by personalising content and banners in real-time on multiple devices. myThings uses these data-driven advertising solutions to increase click and conversions by more than 150 per cent, making your marketing budget go further and providing tangible results.
Having the ability to collect and analyse that data easily, and then turn it into actionable insights that feed back into the business, is crucial in a world where there is so much information available.
Digital marketing businesses like myThings can process 20 terabytes of data daily – that’s the equivalent of 40,000 hours of television downloads. This volume of data is huge, meaning that any data solution used must be able to cope with this sheer amount of data generated from the customers of today as well as the future.
myThings analyses enormous, complex amounts of data on a daily basis with the help of an analytic database. In the case of programmatic marketing, more data is always better, and having access to this means myThings can rekindle the interest of anonymous users for its clients, such as Walmart and very.co.uk, through dynamic banners with truly customised product recommendations.
Up to date and accurate information is critical
Brands now face the pressure of not only being able to analyse vast volumes of data in the first place, but also being able to do it really quickly. There’s often pressure to create immediate return. By identifying relevant data quickly, companies can improve their competitiveness and the performance they deliver to customers. Happy customers = happy businesses = happy marketers.
Anything that takes half a day to process is far too slow for today’s marketplace. Analytical results of complex information needs to be presented as quickly as possible in order for businesses to be able to integrate the findings and inform their strategies. Otherwise you are acting on out-of-date information whilst your potential customer has already looked elsewhere and taken their custom to a competitor.
In today’s digital marketplace, having accurate data analytics can make or break a company. If analytical technology is not applied in the right way, brands risk being left behind and will struggle to remain competitive or even just keep up with the market.
It’s not down to the CMO to become a data scientist and have a handle on the ins and outs of systems and numbers
By having that ability to apply complex data science methodologies, the brand can analyse and determine audiences’ interests and affinities with a truly relevant, personalised approach. In the case of myThings, it also increases the quality and relevance of advertising generated in real-time.
The potential of data analytics doesn’t stop here for programmatic marketing; query times can be reduced for each consumer quite considerably, basket analysis, performance monitoring and reporting are now available in real-time and historical customer data can be saved for extended periods of time.
The skills to pay the bills
Most advertisers don’t have this functional ability to delve into this data and utilise algorithms to gain competitive advantage due to limited tools or a lack of understanding of the benefits. Analytics are usually limited to measurements of performance and understanding what an individual is doing on their website with most still only focused on performance and cost-per-click. But there is no need for them to understand the algorithm and underlying technology behind analytics, just how the campaign is performing.
As marketing and technology progresses, the CFO, CMO and CTO will come together with creativity backed by science and technology, creating real ROI. Brands and marketers have been talking about big data for a while, but the lack of confidence in whether it can truly deliver ROI and allow for accurate personalisation of messages is down to a gap in knowledge and expertise.
Marketers don’t need a data science degree
However, it’s not down to the CMO to become a data scientist and have a handle on the ins and outs of systems and numbers. There are predictive data analytic tools out there that can provide the detailed insights that CMOs are looking for, without the need to be a coder or tech expert. CMOs just need to know that it works, understand the questions they need to ask of the data, and be safe in the knowledge that the technology provides them with the relevant results that they need in an easily understandable format.
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