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5 Practical Use Cases of Data Science in Marketing

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4 minutes, 44 seconds read

Data Science is enormous. It brings forth a scientific approach to gather a massive amount of useful data from raw & disordered information (often collected from open sources). According to recent research, over 2.5 million terabytes of data appear daily. In 2020 every person produces 1.7 MB of data per second. Scientists, Analysts, and numerous other specialists use this data to derive decision-ready insights.

Using data science, marketers can get a clearer picture of their target audience. With this knowledge, any organization’s marketing department can formulate strategies to target customers who portray higher chances of conversion. Also, by delivering values, organizations can eventually maximize revenues. Going with the traditional methodologies, data processing can be a daunting task. Data Science offers a cost-effective solution to businesses seeking data-driven insights.

Let’s delve deeper into 5 most profitable and practical use cases of data science in marketing.

1. Budget Optimization

The primary goal of any marketer is to achieve the highest possible ROI from the allocated budget. This objective is undoubtedly difficult and time-consuming. On top of which, because of changing market dynamics and user preferences, strategies often go off the track leading to unanticipated outcomes.

Data science can be a saviour here. By analyzing the marketing department’s spending and acquisition ratio, organizations can build a model to distribute the budget in the smartest way possible. A clear picture will help marketers to invest money in the most relevant and surplus channels, thus optimizing key metrics.

2. Defining Audience Persona

While every marketer is familiar with the process of building the target audience portrait, determining the exact persona of the potential customer can still be a challenge. The lack of proper data insights might lead to ineffective advertiser decisions leading to a waste of resources.

Data science methods help marketers to understand the user persona and their preferred communication channels with data-driven insights. This means that the marketing budget will be spent on the right channels of influence, ignoring the irrelevant media, which a normal human being will think of covering for “just in case”. Such adjustment will inevitably increase the ROI and optimize the entire advertisement campaign. This will also retain brand relevance to the customers.

[Related: Your shopping cart just got a lot smarter!]

3. Brand New Social Media Marketing Strategy

Social media trends change faster than a human can track it. Facebook, LinkedIn, and Twitter define what is popular, and a marketer has to catch up with the trends.

Data science can keep you on track with the changing trends. Using the logic of Data Science in Marketing, one can get a bigger picture of what type of content people like interacting with. Data science allows us to gather and analyze data about people’s online behaviour. It provides the key metrics to adjust the SMM (Social Media Marketing) goals, which include – the time of posting, content type, amount, etc. These simple adjustments using data science insights can help increase the marketing ROI drastically.

4. Clearer Content Strategy

One of the biggest gaps between planning and execution that marketers face is knowing which channels will be affected and what kind of people will interact with their content and with what sentiment. Will be potential customers? Are interactors content gatherers? Are they the competition? Do they intend to ruin your reputation?

Knowing all this information will help streamline your content strategies.

As long as you know who your customers are; what are their perceptions about your brand; what information can attract/repel your customers; what social channels they are mostly active on; what are their sentiments with your content; what they usually do when they like or dislike a content; you’ll know what type of content you should produce.

For instance, some people hate emails, while others adore reading them. Some people want to resolve their queries publicly on social media, which some care about their online image. Data science can help achieve personalization to some extent, which can help humanize the conversations with your followers.

Let’s take another example of how data science in marketing can help stakeholders. It gives marketers insights about what phrases a customer would use while searching for a product/services online. Marketers can utilize this insight and prepare a content strategy that embeds these terms more often in your posts and articles.

Therefore, we can say that data science brings a variety of actionable insights about customer acquisition channels, their preferences, and engagement style, which can help plan content strategy accordingly.

5. Increasing Customer Loyalty

Your best customers are the ones who will not just purchase your product once but also will repeat buying and bring their friends and relatives to your store. Organizations realize that customer retention is easier than acquiring new customers.

But consolidating loyalty may be tricky. Data science can provide the marketing department with all the necessary information that can help boost customer loyalty. Based on purchase history and current search queries, analysts can predict their customer’s inclination towards a product. Accordingly, brands can create the most relevant offers for their customers. With personalized offers, existing customers feel special and will return to your brand and not go to the competitors.

The Essence of Data Science in Marketing

Using data science in marketing may ease the work of employees and uplift your strategies to new heights. We have to admit that the more structured information marketing teams have, the more effective their strategies become. At the core of any marketing efforts, data science can optimize cost for data processing and result in overwhelming conversion rates.

[Related: 5 Deep Learning Use Cases in Insurance]


About the Author: Marie Barnes is a writer for Bestforacar and an enthusiastic blogger interested in writing about technology, social media, work, travel, lifestyle, and current affairs. She shares her insights with the world through blogging. You can follow her on Medium.

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Retention playbook for Insurance firms in the backdrop of financial crises

4 minutes read

Belonging to one of the oldest industries in the world, Insurance companies have weathered multiple calamities over the years and have proven themselves to be resilient entities that can truly stand the test of time. Today, however, the industry faces some of its toughest trials yet. Technology has fundamentally changed what it means to be an insurer and the cumulative effects of the pandemic coupled with a weak global economic output have impacted the industry in ways both good and bad.

Chart, line chart

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Source: Deloitte Services LP Economic Analysis

For instance, the U.S market recorded a sharp dip in GDP in the wake of the pandemic and it was expected that the economy would bounce back bringing with it a resurgent demand for all products (including insurance) across the board. It must be noted that the outlook toward insurance products changed as a result of the pandemic. Life insurance products were no longer an afterthought, although profitability in this segment declined over the years. Property-and-Casualty (P&C) insurance, especially motor insurance, continued to be a strong driver, while health insurance proved to be the fastest-growing segment with robust demand from different geographies

Simultaneously, the insurance industry finds itself on the cusp of an industry-wide shift as technology is starting to play a greater role in core operations. In particular, technologies such as AI, AR, and VR are being deployed extensively to retain customers amidst this technological and economic upheaval.

Double down on digital

For insurance firms, IT budgets were almost exclusively dedicated to maintaining legacy systems, but with the rise of InsurTech, it is imperative that firms start dedicating more of their budgets towards developing advanced capabilities such as predictive analytics, AI-driven offerings, etc. Insurance has long been an industry that makes extensive use of complex statistical and mathematical models to guide pricing and product development strategies. By incorporating the latest technological advances with the rich data they have accumulated over the years, insurance firms are poised to emerge stronger and more competitive than ever.

Using AI to curate a bespoke customer experience

Insurance has always been a low-margin affair and success in the business is primarily a function of selling the right products to the right people and reducing churn as much as possible. This is particularly important as customer retention is normally conceived as an afterthought in most industries, as evidenced in the following chart.

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        Source: econconusltancy.com

AI-powered tools (even with narrow capabilities) can do wonders for the insurance industry at large. When architected in the right manner, they can be used to automate a bulk of the standardized and automated processes that insurance companies have. AI can be used to automate and accelerate claims, assess homeowner policies via drones, and facilitate richer customer experiences through sophisticated chatbots. Such advances have a domino effect of increasing CSAT scores, boosting retention rates, reducing CACs, and ultimately improving profitability by as much as 95%.

Crafting immersive products through AR/VR

Customer retention is largely a function of how good a product is, and how effective it is in solving the customers’ pain points. In the face of increasing commodification, insurance companies that go the extra mile to make the buying process more immersive and engaging can gain a definite edge over competitors.

Globally, companies are flocking to implement AR/VR into their customer engagement strategies as it allows them to better several aspects of the customer journey in one fell swoop. Relationship building, product visualization, and highly personalized products are some of the benefits that AR/VR confers to its wielders.  

By honoring the customer sentiments of today and applying a slick AR/VR-powered veneer over its existing product layer, insurance companies can cater to a younger audience (Gen Z) by educating them about insurance products and tailoring digital delivery experiences. This could pay off in the long run by building a large customer base that could be retained and served for a much longer period.

The way forward

The Insurance industry is undergoing a shift of tectonic proportions as an older generation makes way for a new and younger one that has little to no perceptions about the industry. By investing in next-generation technologies such as AR/VR, firms can build new products to capture this new market and catapult themselves to leadership positions simply by way of keeping up with the times.

We have already seen how AR is a potential game-changer for the insurance industry. It is only a matter of time before it becomes commonplace.

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