The term’ data science’ is often used interchangeably with data analytics and data analysis. But data science is quite distinct from these. Data science refers to a blend of various algorithms, tools, and machine learning principles that operate with the goal of discovering hidden patterns from raw data. Big data experts make decisions and predictions by using prescriptive analysis, predictive causal analysis, and machine learning. Data analysis or data analytics is the process of applying statistical, logical, and analytical techniques to data sets for discovering information that will aid in making informed decisions. A data analyst uses tools such as data mining, textual data analysis, and Business Intelligence (BI).
Having understood the individual definitions of data science and data analytics/data analysis, let us analyze some of the concrete ways in which data science can be leveraged by companies for successful digital marketing.
Data Science for Digital Marketing
The following are some of the ways to use data science in digital marketing.
1. Boosting Community Presence
Data science can be used for identifying popular topics for community campaigns apart from making them more effective and targeting the right audience. Using the data and keywords that have been collected across various social platforms, data science helps users identify hot topics of conversation. Machine learning and cluster analysis are other tools that can be used by digital marketing teams to identify the ways in which people interact with each other and the manner in which such conversations take place.
2. Identifying the Right Channels
Data science experts help determine the channels that will give the marketer an adequate lift. By making use of a time series model, a data scientist can identify and compare the various kinds of lift seen in various channels. This is highly beneficial as it provides information to the marketer about the exact channel and medium that will deliver proper returns.
3. Marketing Budget Optimization
Marketers always operate under a strict budget. The primary goal of a marketer is to derive maximum ROI from the allotted budgets. It is always tricky and time-consuming to achieve this. Marketers would most often find it difficult to accomplish efficient budget utilization as things may not always go as planned. A data scientist will be able to build a spending model by analyzing the spend and acquisition data of the marketer. This will help utilize the budget in a more efficient manner. This model will help marketers distribute their budget across mediums, channels, locations, and campaigns for optimizing their key metrics.
4. Matching Marketing Strategies With Consumers
To get the maximum value out of their marketing strategies, marketers must match them with the right consumer. For this purpose, data scientists can create a customer lifetime value model. This will help them segment customers on the basis of behavior. Marketers can use this model to send referral codes, and cashback offers to customers of high value. Retention strategies can be applied to users who are likely to leave their customer base.
5. Advanced Lead Scoring
Every lead procured by a marketer does not convert into a customer. If a marketer accurately segments customers based on their interest, it will increase the performance of the sales department and will ultimately boost revenue. Data science experts help marketers create a predictive lead scoring system. This system is an algorithm that has the ability to calculate the probability of conversion and segment your lead list. This list can be segmented into curious prospects, eager customers, and customers who are not interested.
6. Customer Communication
By analyzing data properly, marketers can determine the proper time to communicate with their prospects and customers. For example, this will help them understand that a customer reads and responds to emails but is not very receptive to messages. These insights help marketers understand the right time and channel for communication.
7. Moving Beyond Word Clouds
Marketers relied on word clouds to analyze social conversations. Word clouds are useful in cases of high social activity. Marketers ended up using irrelevant keywords if the level of social activity was low. Using data science and natural language processing algorithms, marketers will be able to go beyond word clouds by delivering meaningful insights and contextualizing word usage.
Conclusion
Nowadays, data is everywhere and is abundant. In the past decade, online information consumption has shot up drastically, owing to the wide affordability of the World Wide Web. As per estimates, there are more than 6 million devices that are currently connected to the internet. Every day, it is believed that 2.5 million terabytes of data are generated. This is a figure that is extremely hard to imagine. This staggering amount of data is a goldmine, especially for marketers. Thanks to data science, companies are now able to properly process and analyze this data that can deliver valuable insights that can be used towards target customers. Data science aids marketers greatly in decoding these huge chunks of data, which can be a mammoth task. Data science thus helps unlock the value of data for any organization. If executed in the right manner, data science is a powerful force for any company.
If you wish to become a big data expert, check out Global Tech Council.
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