Is Data Science the New Enabler for Successful Digital Marketing?
By Arijit Banerjee
In the digital age where voice recognition devices, electric cars and smart homes are a reality, customers interact with brands online, using as many as seven devices every day. Unsurprisingly, companies are upping their investments in digital marketing to reach more customers and prospects. According to a survey Exploring India’s Digital Marketing Landscape, 41% respondents said digital marketing accounts for one-fourth of their total marketing spend and another 24% said it accounted for 25% to 50% of their total marketing budget.
As digital marketing is growing in prominence, so is data science – as it enables digital marketers better understand their customer behaviour and improve engagement by answering several questions. How are customers finding our website? What keywords are they using to get there? How successful was our last digital marketing campaign? Which are the potential target audiences we can go after to expand our customer base?
Let’s take a deeper look at four ways in which marketers can leverage data science to achieve better digital marketing results.
- Identify most commonly discussed keywords using ML
Every second, 3.3 million new posts appear on Facebook and almost half a million on Twitter. ML can help marketers overcome information load given the humongous amounts of data they must process. Using algorithms, ML helps identify patterns and categorize them into clusters such as the number of times a specific brand name was mentioned. Airbnb, for instance, incorporated ML to leverage available data to determine host preferences in order to better match users visiting its website, enhancing customer experience as well as maximizing profits.
- Visualize complex relationship and patterns
Capturing complex data and numbers in a visual format enables marketers and data scientists to collaboratively unearth new opportunities and design future campaigns. For example, tools such as Hootsuite and Domo equip marketers to measure the performance of their social media channels and teams by creating easy-to-understand dashboards. They also allow users to create data fusion between different social media data sources, and assemble and organize data to generate reports with necessary KPIs.
- Use social media listening to build customer personas
One of the most critical questions to ask is - what makes people buy a product or service - a question that can be answered through the science of attribution. Analytics helps identify brand messages that resonate best with a given audience and study customer attributes such as their spending behaviour in order to make superior business decisions. In addition to several social listening tools available in the market, Social media giants Facebook and Twitter have created separate departments for data science. Facebook shares infographics and data analysis such as NFL fan friendships on Facebook while Twitter Data provides infographics and trending twitter moments - all of which can be used to gain deeper insights on customer behaviour.
- Leverage NLP tools to contextualize insights
80% of unstructured data available today consists of textual data. Natural Language Processing (NLP) tools help marketers add more filters to the text to detect patterns that give meaning to the available data. It makes it possible to understand customer sentiment from texts, posts, and tweets to better segment customers. Kohler, the leading manufacturer of home improvement products, was looking to dynamically change its messaging around key events it was sponsoring. Using NLP, the company was able to better understand the online communication style of its attendees at these events, enabling it to realize better ROI from their event sponsorships.
This synergized intersection of digital marketing and data analytics has given rise to the need for skill sets such as marketing analytics, web analytics, and the profile of chief marketing technologist (CMT). According to the survey on Indian digital marketing landscape, 66% of respondents believe that finding talent is the major bottleneck for the digital media industry, which is growing at 40% year on year as compared to 5% to 6% growth in many other industries. Investing in upskilling and training initiatives is one way for organizations to address the skills gap and take advantage of the benefits data science offers to bolster their digital marketing campaigns.