There has been a major verge of research in the data analytics area. According to studies, over 6 billion devices are connected to the internet right now. It is estimated that by 2020, for every single person on the planet, there will be 1.7MB of data generated every second. While people are fascinated by this fact, for marketers, it is a REAL goldmine. If one is able to properly analyze and process this data pool, it has the power to deliver valuable insights which can be used to target customers. Sounds exciting? However, decoding huge chunks of data is a mammoth task. Here’ where data science in marketing analytics plays a role.
What is Data Science?
In a nutshell, data science is a field which is responsible for extracting meaningful information from raw data sets and help deduce an insight over it. Further, these insights can be used in various marketing applications, such as behavior analysis, customer intent, experience, etc. that carries value in optimizing marketing campaigns and strategies in order to derive maximum revenue.
Table of Contents
- What is Data Science?
- How to use Data Science in Marketing Analytics
- 1. Marketing to the RIGHT audience
- 2. Budget Optimization
- 3. Identifying the Right Channels
- 4. Matching Strategies with Customers
- 5. Knowing Lead Intend
- 6. Advanced Lead Scoring
- 7. Customer Personas & Profiling
- 8. Strategy Creation
- 9. Sentiment Analysis
- 10. Product Development
- 11. Customer Communication
- 12. Analyzing Real-time Interactions
- 13. Enhancing Experience
- 14. Social Media Marketing
- 15. Ad Offerings
- 16. Digital Marketing Platforms
How to use Data Science in Marketing Analytics
Here’s a list of practical applications of data science in marketing analytics,
1. Marketing to the RIGHT audience
The major pain that almost every marketer encounters in to get the exact match of the desired audience. And as a result, a major portion of the marketing budget is wasted. To avoid this and in order to make achieving the ideal ROI percentage, revenue targets, goals, etc, one may employ the use of data science in marketing planning.
However, you must employ its usage to analyze the key segment of data first, for eg, understanding the demographics and overlapping interest groups to achieve the highest ROI.
2. Budget Optimization
Admit it. You always lack the appropriate budget that is needed to achieve marketing set goals. Still, you are expected to deliver maximum ROI over that allotted budget. Achieving this is at times always a tricky and time-consuming task. A major reason is that things don’t always go according to the plan and you are required to opt for budget optimization as a choice.
Using data science, you could analyze your spend and acquisition data in order to utilize the budget better. You could create your own mix of various metrics like location, channel, medium, spend, etc, and optimize them accordingly to get results.
3. Identifying the Right Channels
Ever experience a stage where a few channels perform much better as compared to others. Data science can be used to determine which channels are giving a lift to the marketing efforts and which aren’t. You may employ time series model of data science, to identify the kinds of lift in your channels. This can be very advantageous as you’d know exactly which channel and medium are delivering higher returns.
4. Matching Strategies with Customers
“You need to know what your customer needs and deliver the same to them”, a well said one-liner. As marketers, we need to know what an ideal customer needs, what are his/her expectation, what sort of experience do they as ‘customers’ crave!
To do this, data scientists have invented a customer lifetime value model that could be used to segment customers on the basis of their behaviors. Further, you could use this model for various applications, eg, to send referral codes & cashback offers to the highest value customers, identify the most friendly offers that customers use and retarget them using these, etc.
5. Knowing Lead Intend
You may use data science to narrowly target leads and generate data to know all about their online behavior. You may also analyze their historical data, casual inclination towards a particular brand/product and types of brands they’ve been associated with in the past.
6. Advanced Lead Scoring
Every lead that you procure doesn’t really converts into a customer. If a marketer accurately segments customers on the basis of their interest, it would help the sales department to become more proactive towards the conversion, and ultimately, increase the company’s revenue.
Data science would allow marketers to create a predictive lead scoring system. This system would be capable of calculating the probability of conversion and segmenting your lead list on a priority basis. The priority could be classified like, eager customers, curious prospects, and not interested customers.
7. Customer Personas & Profiling
As marketers, one of your roles includes creating customer personas for the benefit of your brand. For this, you are always in a rush towards building specific lists of prospects to target. With data science, you could accurately and more precisely decide which personas need to be targeted. By this, you will be able to develop the kind of characteristics you need to create your customer base.
8. Strategy Creation
You need to have a good strategy in order to grab eyeballs over your offered service/product. Data science can help pull customer’s data that will, in turn, help you in creating content the best version of the content for every customer. For eg, if you know that a customer came via Google search, you know what would be his/her intent by analyzing data for that particular keyword.
9. Sentiment Analysis
You can use data science to conduct sentiment analysis. Period. This means that data science could lead you through in knowing insights over your customer’s belief, opinion, attitude, and emotional inclination. Also, you could monitor how customers are reacting to your campaigns and determine how they are choosing to engage with your business.
10. Product Development
Data science can be used to gather, aggregate, and synthesize data on various aspects of a product, even for different demographics. Based on insights of this fetched data, you could modify your product offerings in a coherent way and create more specific campaigns for the intended demographic.
11. Customer Communication
Using an adequate amount of analysis, marketers can determine the right time to communicate with your potential prospects and customers. Eg, your customers might be more proactive over email communication in the afternoon as compared to the morning or evening slots, which makes the afternoon slot most appropriate to deliver marketing campaign emails.
Such insights would make the expected ROI a bit more efficient and also, speed up the customer service process.
12. Analyzing Real-time Interactions
Majority of the customer desire instantaneous support, marketers often exploit this channel by promoting real-time events or offers to them. Data science can produce information about such events and help predict consumer behavior on such an encounter.
For eg, a travel company could make use of such events via sending push notification to their first-time prospects about a 5% discount offer to drive them towards making a sale and helping them convert into a customer.
13. Enhancing Experience
Delivering rich customer experience has always been an important winning factor for brands like Amazon. Using data science, marketers can collect user behavior patterns and identify what sort of products a potential customer would need and generate a specific trail for them to follow. This trail would allow you to market efficiently and deliver enriching experiences to your customers.
14. Social Media Marketing
Each customer is active on social media sites like Twitter, Facebook, Instagram, etc. You could use data science to see which leads are exploring your company’s social media feeds, what sort of content are they engaging with and what is their inclination towards a product. Using such insights, you could formulate a proper social media strategy for your brand.
15. Ad Offerings
You may use data science to specifically target ads to customers and measure clicks and results of campaigns by gaining insights on which ads are performing the best. The easiest way to do this is by creating A/B tests for your campaign and analyzing what keeps your audience engaged.
16. Digital Marketing Platforms
Digital marketing platforms thrive on data. Data science in digital marketing can garner better insights by feeding these platforms with refined data. Further, it could improve digital marketing platforms by providing the right data and thereby enabling marketers to determine what they have to do to achieve their marketing goals.
The application of data science in marketing analytics seems exciting, right? Well, there’s a lot more which you could achieve if you are able to just get the right hold of it. And while the field is still developing there’s a major unexplored segment left off… test it and comment below if you know any other implementation.
You may also like,