DATA SCIENCE IN MARKETING
Posted on 19-Jan-2021
Brands are collecting an extensive amount of data at various stages of the customer journey. Data science helps us leverage this data into actionable insight that results in a greater return on investment. Data science methods like machine learning, clustering, and regression have moved marketing from a creative domain to a scientific one. By leveraging data science, marketing teams can extend their top-funnel approach to incorporate the full-funnel and uncover product and customer insights at scale in an unprecedented way.
WHAT DATA SCIENCES IS OR IS NOT?
Specifically, people often interchange the terms of data science and data analytics and there is a lot of confusion for the role and profile of data sciences and what they do. The easiest way to differentiate between the two is that a data scientist looks to predict the future, while a data analyst looks to summarize the past.
Data scientists make predictive models using regression, machine learning, and other advanced statistical methods, while a data analyst uses descriptive statistics to analyze past patterns.Data science is the intersection between business expertise, programming, and statistics, where programming is simply a medium to derive insights using statistics and business or domain expertise.
The data scientist toolbox uses artificial intelligence and mathematical modeling to unlock a new set of insights. Who are your most promising customers? What choice alternatives do consumers of your product have? How do people feel about your brand? What other products do your customers want to buy? The above mentioned are some of the questions which a data scientist can answer easily.
HOW DOES DATA SCIENCE WORK?
The best way to grow your results is that the marketing team of your company needs to indulge with the data scientist and their measurements. Data scientists have a profile of giving great insights to the company and also giving great research and engagement details. This could mean testing models on historical data sets and measuring its accuracy or a variety of other methods to create a benchmark against which to measure the success of whatever model we pick. After the model is chosen, the data is formatted in a workable way.
A growth marketer is well aware of its work and profile that they everytime seems to have an example to how to grow business and sales. tying a business’s marketing strategy to key performance indicators like customer lifetime value, incrementality, and cost per customer acquisition is absolutely necessary for a competitive business landscape.
A favorite tool of every data scientist and one that is absolutely necessary to the modern-day marketer to help with this is segmentation.
KEY BENEFITS OF SEGMENTATION
- Determines Market opportunity
- Insights
- Great marketing initiative
- Product development
A business can forecast the customer lifetime value of new customers through the use of several machine learning and artificial intelligence methodologies. Rather than just focusing on a first sale, growth marketers employ data science insights to help companies to target longer customer relationships. Data science allows you to understand the customer journey in a much deeper way than previously possible. Data scientist gives you the best relevant information regarding you company and customers. Where do your best customers come from? Data scientists give you the insights to curate your marketing strategy to the customer that makes the most sense for you. Your marketing team is now working on retention. This works all the way down to referrals. Artificial intelligence can help you determine which customers are influencers for your brand through qualitative analyses on the quality of content, brand affinity, and brand engagement.
Marketers and data scientists alike know that at the end of the day, data is really about understanding people. In the age of social media, businesses have access to unfiltered, unbiased, real-time commentary from their customer base and people exposed to their brand.
A simple sentiment analysis will give you an idea of how the public feels about your product. Most commonly for marketing, this is done through polarity, meaning words are assigned a value of positive, negative, or neutral.
INSIGHTS AND EXPERIMENTATION
Data scientists look for causal relationships that growth marketers can then reverse engineer into an effective campaign. The data scientist can test if that is true with a regression analysis, then the growth marketer, in partnership with the data scientist, can come up with experiments to test which campaigns produce more clicks, therefore a higher conversion rate.
Sometimes marketing gives great risk to the companies. This requires some level of risk, but with our data science toolkit, that risk is minimized. In the business world, we often get caught up in the “best practice,” rhetoric, when in reality, every business we have seen scale has done so by taking risks.
SHOULD YOU HIRE A DATA SCIENTIST?
Before hiring a data scientist the companies should consider that data scientist should be asking themselves questions like do I have enough data? Is that data sourced in a way a data scientist can access? An early-stage startup may not have the infrastructure or volume of data to necessitate hiring a data scientist. Data scientist are always loyal towards the company and always deliver accurate and exact data to the marketing team or company admin.
As is in marketing, when thinking about where to integrate data science and growth marketing tools into your marketing strategy, it is often best to capitalize on the low hanging fruit first. Certain tools and methods are easy to implement using data your company is already likely to have.
Few top most company which almost uses data scientist as to grow their customer and clients respectively
The companies are:
- Netflix
The future is growth. Growth marketing is not just marketing for startups or scaleups; growth marketing is about optimizing your progression as a business. For a large enterprise, that might mean developing a new product to maintain your position. For a startup, it might mean driving conversion rates on your company’s website. Companies like Google, Facebook, and Netflix have created a new position in their marketing departments called the growth data scientist to find the insights while the growth marketer applies them.
