The value of data has become increasingly prevalent over the past five years. From increasing sales to driving better decision-making, the benefits of data come to any team in any industry that chooses to invest in new technologies. Harnessing the power of big data is typically left to data scientists, and companies are now scrambling to hire those equipped to collect and analyze data.
Marketers are now relying on data-driven campaigns to meet client goals better and reach their target market more effectively. Marketers are therefore pushing to learn more about data and analytics to improve campaigns and stay competitive in the market.
One study found that companies plan to shift marketing budgets and put more resources toward analytics. Over the next three years, the study notes, the percentage of marketing budgets allocated to analytics will increase from 5.8 percent to 17.3 percent, which shows a 198 percent increase. This should come as no surprise, as only 1.9 percent of marketing leaders said they have the right talent to leverage marketing analytics.
Since marketing leaders currently lack qualified candidates to use the power of data fully, and since companies plan on allocating more marketing resources to analytics, it begs the question: Are data scientists taking over marketing teams?
Where is data most useful in marketing campaigns?
Before answering that question, it’s important to break down where data can help the most in marketing campaigns. Of course, this depends on the type of marketing each company performs and the end result, but these are common areas of marketing campaigns that data can improve.
There’s a significant shift in the marketing world from “I think” to “I know.” Clients and executives no longer want to hear that marketers think something about a buyer. They want to know. And the only way to know something about a buyer is by using data.
One way to know more about a buyer persona group is through social media listening. Considering the vast amount of public conversations that happen on social networks, marketers have the ability to analyze a lot of data. Data tools can collect consumer thoughts and segment these thoughts by demographics. This process transforms the I think to I know quickly and gives marketers real insight into consumer thoughts and behavior on social sites.
Currently, common marketing practice is to measure the results of a campaign after it ends. At that point, marketers have either met client goals or they have not. This practice, however, is outdated and, thanks to data tools, marketers can measure how campaigns are working in real-time and adjust tactics accordingly.
For example, instead of disappointing clients by not meeting goals at the end of a marketing campaign, marketers can measure how well a campaign is doing earlier on and set expectations. If a certain project aims to gain X amount of marketing-qualified leads, marketers can measure how far along they are at various points of the campaign instead of simply looking at the end.
Data can also help marketers create more powerful pieces of content that push prospects down the sales funnel to generate more MQLs. Through big data, marketers can measure content aspects such as calls to action and read-through rates, learning what content is effective and what is not. Then, the team can replicate useful posts to push prospects to complete their goal.
To take campaigns to the next level, marketers can use predictive analytics. Instead of watching past behavior to predict what a consumer will do next, predictive models can forecast consumer trends with much more accuracy. Marketers can take this information and plan strategic campaigns around it.
Predictive analytics have value in all sorts of marketing tactics such as advertising, content strategy and social media. Of course, this type of modeling is highly sophisticated and takes trained data scientists to create, implement and analyze.
Who will run this data?
The value and necessity of data in marketing campaigns are clear. So, who will manage this data? Will marketers train themselves to become data-savvy? Or will executives skip the training and hire data teams to run marketing campaigns?
The answer is likely a bit of both. Marketers that learn how to read and analyze data will clearly be in demand as they can blend old-school marketing practices with new, innovative technologies. Data scientists, specifically trained in data analysis and data analytics, will likely join marketing teams in leading roles to improve campaign performances.
Of course, the large companies that can both train their marketing teams in data and add high-level data scientists to the company will do so. However, for small and midsized businesses, and for most marketing agencies, executives will expect marketers to pick up the data slack and learn how to integrate big data into existing campaigns.
Marketers must be aware of the movement toward data-driven decisions and campaigns and prepare themselves for this shift. Those that do not train themselves in data will lose market competitiveness and likely find themselves without a place on future marketing teams.
Jennifer Roubaud is vice president of the U.K. and Ireland for data science software platform provider Dataiku.