Data Science A New Trend Of Marketing & Research

Written By: Melissa Calvert

Posted on: October 10, 2019

Online data consumption has shot up drastically over the last ten years. The reason is the overall affordability of the web across the world. To date, it is estimated that over 6 billion devices are cone ted to the internet, and approximately 2.5 million TB of data is generated daily on the internet. With this exponential growth, there will be 1.7MB data created by every single person every second by 2020. 
Fortunately, the staggering big data is a gold mine for marketers. The information has the potential to deliver valuable insights if processed and analyzed usefully. Also, it can be beneficial to target customers by segmenting them. However, grouping and decoding massive data chunks is tough work. That’s the place where Data Science can help marketers. 
Considering marketing, data science extracts relevant information from the massive pile of data and helps marketers in sagacious insights. They can drive opportunities for analyzing customer’s experience, intent, needs, and behaviors that help them to optimize strategies and generate revenues. 

Data science

Below are 21 ways Data Sciences can be beneficial for marketers. 

1. Customer Profiling

Creating a customer’s persona is the first step while marketing a product or a service. Marketers consistently built specific lists of customers for targeting. Data sciences can help then to figure the accuracy of a customer’s persona to target their needs. They can filter from and figure out a variety of personas to check for their desired traits for creating a customer base. 

customer profiling

2. Content Strategy

Marketers are bound to deliver valuable and relevant content to engage their clients. Data sciences can leverage them by getting consumer’s interests, needs, and pain points that may help them to create the best content for them that they love to read. Hence, if a customer is searching for a specific keyword in the search engines, marketers can use that keyword appropriately in their content.

3.   Budget Optimization

The dilemma with marketers is that they have to work on a strict budget. They are bound to drive maximum ROI from the allocated budget. Hence, achieving the bottom line is always time-consuming and tricky. Mostly, things may not go as per plan, and thus, effective and efficient utilization of budget is not achieved. 
Data science can help to create a spending model by analyzing a marketer’s data for acquisition and spend, which provides better budget utilization. Spending model lets marketers distribute budget across a variety of channels, locations, mediums, and campaigns to optimize key metrics of their advantage. 

budget optimization

4. Targeting Audience

Marketing campaigns are distributed on a wide array of customer base irrespective of socio-economic norms. That is why there are high chances for overshooting of budget. As a result, they may not be able to achieve their targeted revenues. Here, data sciences can be used to analyze customer’s demographics and let marketers understand the best groups to generate a high ROI.

5. Identifying the right channel

Undoubtedly, data science has an edge in determining the adequate channel to give a lift for marketers. Marketers can identify and compare with the help of the Time Series Model to determine the lift in various channels. Data science can serve with a high benefit to the marketers by telling them which channels are delivering profitable results. 

6. Align Strategies with Customers

It is essential to align marketing strategies with the customer’s needs to drive the maximum value out of your investment. With the help of data sciences, marketers can create a lifetime value model to segment their targeted customers based on their behaviors. 
The model can be used for several tasks, including cashback offers, sending referral codes, offering additional incentives, and giving discounted coupons to their high-value consumers. Retention strategies can also be made for those customers who are likely to leave their consumer base. 

7. Lead Targeting

Data sciences can be relevantly used by marketers to narrow down the online behavior and intent of targeted leads. Historical data can help marketers to determine the requirements and purchase behaviors of businesses and consumers along with the type of brands and products they were associated with in the past. 

8. Lead Scoring

No one can deny the universal fact that every lead doesn’t convert successfully into a consumer that a marketer procures. An accurate segmentation can reduce the chances of failure and increase sales performance that leads to revenue generation. 
Marketers can create predictive lead scoring with the help of data sciences. The system can work on algorithms that can calculate the profitability of conversions and segmenting leads. These valuables may include curious customers, eager customers, and not interested prospects. 

9. Customer Experience 

To achieve success in marketing, the most important factor is providing your customers with rich experience. Data science support marketers to trace behavior patterns of their prospects, and it helps them to predict a need specific product for them. This enables them to provide customers with an enriched experience to market things efficiently. 

10. Customer Loyalty

Having a pool of loyal customers is the dream for many businesses. They help to make a business sustainable and are often less expensive when compare to new client acquisition. Marketers can improve marketing to their loyal customers and boost loyalty in existing non-loyal customers with data science. They can target these customers in need of the product and lead them to get influenced by their purchase decision. This type of strategy is proven to turn out a huge success to get back and retain loyalty and business for an organization. 

11. Social Media Marketing

Today’s customers are highly active on social media, including Twitter, LinkedIn, YouTube, and Facebook. Data sciences can leverage marketers to explore leads interested in their social media updates and what kind of content they are liking and sharing. Such insights can help them to formulate a smart social media marketing strategy. 

12. Sentiment Analysis

Data science can be ideally used for sentiment analysis. It enables marketers to get better insight into their customer’s opinions, beliefs, and attitudes. It can track how a customer is reacting to their marketing campaigns and if they are succeeded in engaging them. 

13. Product Development

Marketers can aggregate and synthesize data concerning their products based on a variety of demographics. It makes sure to let them develop those products that are needed with a highly targeted marketing campaign to their intended needs. 

14. Pricing Strategy

Here comes the most discussed marketing factor, money. Marketers can plan and improve their pricing strategy with the help if data sciences. It lets them concentrate on the client’s individual factors, including purchase history, preferences, and economic situation, to identify those factors which drive them and the price along with a customer’s buying behavior. Undoubtedly, price is the most critical driving factor which affects consumer’s buying intent for a particular product segment. 

15. Customer Communication

Successful customer segmentation is incomplete without a thorough communication. Marketers can analyze data obtained to get the perfect time and way to communicate with their customers. Also, it can suggest the right medium to engage with them. Some like to be communicated on phone calls, some on SMS while others on emails. Get them on their preferred medium to understand and get an expected response. 

16. Real-Time Interaction

You can track a real-time interaction of events easily with data sciences. It enables marketers to tap those happenings to target customers. The idea can benefit many businesses, including hoteling, traveling, and utilities. Hence, marketers can directly send a targeted message to their mobile devices with an ad campaign directly to them. 

17. Email Campaigns

Just like A/B testing, data sciences are much beneficial to figure out which email is successful in getting attraction by most customers. The frequency of reading them gets the perfect time to increase the chances of opening. This will help marketers to create a perfect email campaign that resonates well with the customers. Also, such metrics helps them to shoot out contextualized emails to target clients with the right offers. 

18. Community Groupings

Particular social media groups can be focused and targeted to access customer’s feedbacks and reviews. Marketers can identify and track most discussed, liked, and shared trending topics analyzing keyword research and frequency. 

19. Ad Offerings

Targeted ads can be used to measure clicks and customer engagement to get the most desired results of campaigns. It makes sure that the right banner ad is placed in front of the right prospects. This increases the chance of being clicked. 

20. Digital Platforms

Digital marketing thrives on data and survives on metrics. Marketers can get better insights with refined data. It helps to improve digital marketing strategies and leads them to achieve their revenue goals. 

21. Going Beyond Word Clouds

Marketers can happily rely on word clouds. However, they are useful with a high level of social activity. If there is less activity, it can false perceive with irrelevant keywords. Data science can contextualize those word usages and deliver authentic results for language processing. 

Above are just some of the practical ways to use data science as the new trend in digital marketing. Possibilities are endless, just need an implementing opportunity to prove its worth.