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How We Can Use Data Science In Marketing?
You must have heard over a billion times about Data Science. But I say, you strictly need second thoughts if you believe that Data excites only Data Scientists. No single domain is bereft of this Midas (Data) Touch and for the course of this article “Marketers’ will be the wood to our fire.
Yes, you read it right. All the data obtained from customer interaction and behavior is a jackpot. When processed and analysed in the right manner, you get a lottery. Before all you marketers get excited (which you definitely should), let me tell you that you still need a Data Scientist.
The data collected from marketing operations is colossal, gargantuan and every other imaginable synonym of HUGE. While marketers are expert in strategy designing, optimization and delivery; data scientists excel (pun intended) in handling, manipulating and extracting meaningful insights out of that data.
These analyses cater to customer intent, approach, buying behavior and everything in between. From awareness to revenue, an in-depth acumen will give you all. So just get on-board and we shall set sailing to see the Top 10 Applications of Data Science in Marketing.
By the way, did you notice my deliberate use of alliteration in the previous line?
Consumer Profiling
Thousands of customers shop for the same product but none of them is same. A marketer needs to be well-versed with the profile of his consumers and the characteristics that sets each customer apart. Based on these characteristics, data science can help leverage the interest and liking of each prospect and accordingly deliver optimized results.
Real Time Interaction Marketing
Tapping into real-time information is always a boon. It gives you optimization at its very best. Marketing for a holiday resort, you could collect data about customers who have booked a flight to a city where your resort is and then accordingly target your campaigns to that customer. Real-time marketing with data science gives you an increased scope of converting customers in a thin time frame.
Lead Scoring
The most challenging and probably the most frustrating stage of marketing is to convert a lead into a customer. It is about how well you drive him/her down the funnel.
Once generated, the same customer will provide a template for prediction of lead conversion. A lead showing likely behavior to a converted customer is possibly going to convert and hence could be paid more attention to. On the other hand, a lead showing contrasting features to a converted one may not necessarily come down the funnel.
Marketing Budget Optimization
You know what, you can be an unapologetic miser marketer with data science at your disposal. It will bless your general budget schedule to get distributed performance-wise for each channel, medium, and type of campaign that you are running.
So now you don’t have to exhaust your budgets unnecessarily. Sit back and enjoy – your bills are being taken care of.
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Precise Market Targeting
In case of wide campaigns with a general audience targeting, it is very likely to see mediocre results. The targeting can be made tighter for the audience which is more responsive and interested in a given product.
Data Science can help identify such demographics, locations and interests that will ensure precise reach of campaigns.
Automated Digital Marketing
What else could be better than automating the complete digital marketing process? Now that digital marketing is strongly competent to traditional marketing and has better scope for reading customer data, automating the process will save time and increase efficiency.
Most of the advertising platforms like Facebook Ads, Google Ads uses machine learning to automate their marketing tasks.
Email Campaign Classification
Email Marketing is one of the most popular and effective marketing solutions known to us. Data Science simply studies this solution to identify the response and attitude towards a particular campaign.
It provides an analysis about the type of content that a customer prefers and suggests ways to improve email interactions.
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Pricing Analysis
Customers always believe in paying a justified price for the product they buy. A volatile entity such as price could be best handled by Data Science.
It gives due consideration to attributes such as customer inclination, buying history, market scenario etc. to generate a fair price. That way a marketer is bound to have an adaptive and intelligent pricing strategy.
Customer Sentiment Analysis
Besides being a popular beginner project in Data Science, Sentiment Analysis can work wonders for marketers. It is a simple way of seeing how a customer feels regarding the company’s product or idea.
Marketers can use this to become better aware of their customer’s reactions, opinions, beliefs, attitude and interest.
Contextualizing Word Usage
With loads to do and lots to handle, marketers always look for relevancy and precision. They surely don’t want to waste resources on an irrelevant target. Data Science uses NLP to contextualize the usage of specific words in every situation thereby helping the marketers to target their audience effectively.
And the list could continue till we (the consumers) keep spurring out oil. Mind you marketers, you are about to make a fortune too good for any oil merchant. That too, without a war!
Dear Marketers, please arrange an appointment with Mr. Data Science at the earliest to make life easy (easier).
