IDC predicts that by 2022, Big Data and Analytics will generate $274.3 billion. To put things into perspective, investments in data science is increasing. If you’re a marketer, you must look at your data science investment for a favorable return. Shouldn’t you?
Data science in marketing
The data science industry is growing, leaving no business function untouched. Marketing has turned out into an enormous use case for data science. From analyzing customer behavior to product pricing –data science is becoming extremely helpful. In the past decade, marketing has been purely driven by data. Whether it’s building customer personas based on data or analyzing customer’s sentiments – data is playing a central role in building marketing strategies for organizations around the world.
Here are some popular use-cases of data science in marketing that organizations are implementing —
1. Marketing funnel analysis – Right from the top of the marketing funnel (lead generation) to sales, data science can breakdown customer behavior and reveal what could be improved.
2. User profiling – You can track customer random behavior across the web and use it for further advertising.
3. Advance segmentation – customer segmentation based on demographics, region, etc is an old technique. With data science, you can factor in minutest change including recent life events, birthdays, etc.
4. Price strategy—Pricing strategy should beyond traditional factors like manufacturing cost, competitor’s price, etc. Uber’s dynamic pricing is an example of how data science can be used to charge customers based on real-time events (based on current supply-demand).
5. Lead scoring – Not all leads are the same. Some have better chances of converting than others. Data science does better work at scoring leads than traditional methods.
Data science is creating opportunities for marketing optimization every passing day. Investing in data science clearly is an opportunity that businesses don’t want to miss. Opportunities to capitalize on are definitely here, but marketers should be conscious and take hiring data scientists with a pinch of salt, it can be tricky.
Investment in data science is hefty. So to hire a data scientist for marketing should be thought out strategically.
What to look for in a data scientist?
Hiring a data science professional for marketing isn’t the same as hiring for other marketing roles. When you hire for a data science role ensure that the candidate understands marketing very well. For instance, while working on a content strategy it is imperative that the data scientist is familiar with SEO and search engine functioning. Similarly, the candidate should be familiar with email marketing and so on.
Today all leading organizations are inspired by data-driven business processes. The marketing function is moving from guesswork to data-centric approaches. So much has changed in the past few years, not leveraging data is letting go of opportunities. Progressive organizations have already taken the guesswork out of all their functions.
Having a data science professional in your marketing team can make a huge difference. Don’t you think?