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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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Enhancing digital patient experience with healthcare chatbots

5 minutes read

Chatbots are fast emerging at the forefront of user engagement across industries. In 2021, healthcare is undoubtedly being touted as one of the most important industries due to the noticeable surge in demand amid the pandemic and its subsequent waves. The Global Healthcare Chatbots Market is expected to exceed over US$ 314.63 Million by 2024 at a CAGR of 20.58%.

Chatbots are being seen as those with high potential to revolutionize healthcare. They act as the perfect support system to agents on the floor by providing the first-step resolution to the customer, in terms of understanding intent and need, boost efficiency, and also improve the accuracy of symptom detection and ailment identification, preventive care, feedback procedures, claim filing and processing and more.

At the outset of the COVID-19 pandemic, digital tools in healthcare, most commonly chatbots, rose to the forefront of healthcare solutions. Providence St. Joseph Health, Mass General Brigham, Care Health Insurance (formerly Religare), and several other notable names built and rolled out artificial intelligence-based chatbots to help with diagnostics at the first stage before a human-human virtual contact, especially while differentiating between possible COVID-19 cases and other ailments. The CDC also hosts an AI-driven chatbot on its website to help screen for coronavirus infections. Similarly, the World Health Organization (WHO) partnered with a messaging app named Ratuken Viber, to develop an interactive chatbot for accurate information about COVID-19 in multiple languages. This allowed WHO to reach up to 1 billion people located anywhere in the world, at any time of the day, in their respective native languages.

For Care Health Insurance, Mantra Labs deployed their Conversational AI Chatbot with AR-based virtual support, called Hitee, trained to converse in multiple languages. This led to 10X interactions over the previous basic chatbot; 5X more conversions through Vanilla Web Experience; Drop-in Customer Queries over Voice Support by 20% among other benefits.

Artificial Intelligence’s role in the healthcare industry has been growing strength by strength over the years. According to the global tech market advisory firm ABI Research, AI spending in the healthcare and pharmaceutical industries is expected to increase from $463 million in 2019 to more than $2 billion over the next 5 years, healthtechmagazine.net has reported. 

Speaking of key features available on a healthcare chatbot, Anonymity; Monitoring; Personalization; collecting Physical vitals (including oxygenation, heart rhythm, body temperature) via mobile sensors; monitoring patient behavior via facial recognition; Real-time interaction; and Scalability, feature top of the list. 

However, while covering the wide gamut of a healthcare bot’s capabilities, it is trained on the following factors to come in handy on a business or human-need basis. Read on: 

Remote, Virtual Consults 

Chatbots were seen surging exponentially in the year 2016, however, the year 2020 and onwards brought back the possibility of adding on to healthcare bot capabilities as people continued to stay home amid the COVID-19 pandemic and subsequent lockdowns. Chatbots work as the frontline customer support for Quick Symptom Assessment where the intent is understood and a patient’s queries are answered, including connection with an agent for follow-up service, Booking an Appointment with doctors, and more. 

Mental Health Therapy

Even though anxiety, depression, and other mental health-related disorders and their subsequent awareness have been the talk around the world, even before the pandemic hit, the pandemic year, once again could be attributed to increased use of bots to seek support or a conversation to work through their anxiety and more amid trying times. The popular apps, Woebot and Wysa, both gained popularity and recognition during the previous months as a go-to Wellness Advisor. 

An AI Wellness Advisor can also take the form of a chatbot that sends regular reminders on meal and water consumption timings, nutrition charts including requisite consultation with nutritionists, lifestyle advice, and more. 

Patient Health Monitoring via wearables 

Wearable technologies like wearable heart monitors, Bluetooth-enabled scales, glucose monitors, skin patches, shoes, belts, or maternity care trackers promise to redefine assessment of health behaviors in a non-invasive manner and helps acquire, transmit, process, and store patient data, thereby making it a breeze for clinicians to retrieve it as and when they need it.

Remote patient monitoring devices also enable patients to share updates on their vitals and their environment from the convenience and comfort of home, a feature that’s gained higher popularity amid the pandemic.

A healthcare chatbot for healthcare has the capability to check existing insurance coverage, help file claims and track the status of claims. 

What’s in store for the future of chatbots in Healthcare? 

The three main areas where healthcare chatbots can be particularly useful include timely health diagnostics, patient engagement outside medical facilities, and mental health care. 

According to Gartner, conversational AI will supersede cloud and mobile as the most important imperative for the next ten years. 

“For AI to succeed in healthcare over the long-term, consumer comfort and confidence should be front and center. Leveraging AI behind the scenes or in supporting roles could collectively ease us into understanding its value without risking alienation,” reads a May 2021 Forbes article titled, The Doctor Is In: Three Predictions For The Future Of AI In Healthcare. 

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