The foray of data science into the consumer marketing space has come with some turbulence. Perhaps the most infamous instance comes from 2012, when Target identified a pregnant teenager based on her purchase data.
In the years since, data science has found a sweet spot when it comes to consumer tastes.
- Spotify Wrapped – At the turn of each new year, streaming giant Spotify releases statistics around your listening habits throughout the previous 12 months. Not only who you listened to most, but how much you listened to an artist compared to others.
- Personalized Google restaurant recommendations – Visit a new city and Google will recommend restaurants based on your tastes. You can see if you’ve been identified as a lover of unique cocktails or eclectic gastro pubs.
- Predictive text – Email, text, and other platforms can predict what you’ll say next based on your individual language habits. While some tools can only predict a word or two, others can make predictions of ten words or more at a time.
Today, data science is changing the landscape of how products are marketed to consumers.
Every industry is becoming a data-driven industry, as they search for ways to use data to reach their audiences. This increased focus on data is having a significant impact on data related roles within organizations. By 2030, the Bureau of Labor and Statistics predicts the job market for data scientists will grow by 22%, almost three times faster than the average.
Even non-technical business leaders are seeking out data science certifications to help them suss out how they can use data to achieve broader objectives. Today, there are a few common AI and machine learning tools in the marketplace that help companies achieve record success, and help customers find their next favorite product.
Table of Contents
- Recommendation Engines
- Retargeting Advertisements
- Natural Language Voice Searches and IoT
- Big Data for the Bigger Picture
Recommendation Engines
Almost everyone has logged on to their Netflix account, or other streaming service account, and been greeted by a list of recommended movies and television shows custom tailored to their tastes. With over 5,000 titles to choose from, Netflix’s algorithm, called the Netflix Recommendation Engine (NRE), uses data science to analyze your viewing behaviors and make predictions about what’s likely to keep you watching.
This algorithm is so successful that it drives over 80% of all Netflix viewing choices.
Netflix is far from the only company to leverage data to personalize recommendations to keep their customers engaged coming back for more. Nor is it only internet streaming companies using recommendation engines as part of their marketing strategy.
Many popular and successful companies rely on the data science driving recommendation engines, including familiar big tech companies such as Amazon, YouTube, and Facebook. But did you know that these data-driven recommendations are also being used in banking, hospitality, and many other industries today? In fact, most e-commerce sites, whether B2B or B2C are using recommendation engines to improve customer engagement and retention, ultimately driving more ROI for companies and more satisfaction for their customers.
Retargeting
Data scientists provide tremendous value to companies’ marketing efforts by helping them optimize their retargeting. Data science allows companies to create highly personalized ads with insights gained via product and user data.
Manual retargeting, even with the use of historical analytics, can lead to many missed opportunities and increased spending. Whereas retargeting driven by data science automation can drastically improve conversion rates.
Data can also be used to predict which products someone is likely to purchase based on how they interact with a business and its ads.
Retargeting can be optimized using data science to segment and target those who are most likely to engage with a brand, based on those who visited a company’s website or social media page. Using predictive data allows a business to retarget their audience in a way that feels natural and doesn’t annoy potential buyers or waste impressions on those unlikely to become conversions.
Natural Language Voice Searches and IoT
The Internet of Things (IoT) has grown in popularity in recent years, including the use of smart home systems like Amazon Alexa and Google Assistant. Statistics show that there were 258.54 million smart homes in 2021.
Marketers have long used keyword research to get the most out of their Search Engine Optimization (SEO) when it comes to how their audience uses Google searches.
However, with more and more people using voice activated technology like Alexa to conduct internet searches, it’s less about keywords and more about natural-language voice searches. This is because people don’t speak in keywords, but rather conduct voice searches in the natural way of speaking they would use to hold a conversation with another person.
This adds nuance to how businesses can leverage search data for their marketing efforts, giving them a better understanding of a customer’s intentions, allowing content to be better tailored to what that customer needs.
Technology that utilizes IoT can provide businesses with a plethora of real-time data points that help them understand how customers use these devices in their homes, as well as how they interact with the internet when accessing it via their devices.
Data scientists use this data to create predictive models that can help with creating highly personalized and timely marketing content based on buyer behaviors, as well as aid with other business goals such as research and development.
Big Data for the Bigger Picture
Data science will only grow more essential to companies in marketing and other facets of their overall success in today’s digital economy, especially as technology becomes more complex and AI and machine learning become more ubiquitous in business operations.
Many companies today are collecting a tremendous amount of data about potential leads when it comes to personal information, engagement and buying behaviors, and other metrics about how an audience engages with marketing materials.
Data science allows business leaders to get the most out of this data and to build a marketing strategy that’s cost efficient while driving more conversions and improving customer retention.
A data science certification can help you foster these valuable skills and become an asset in helping your team gain critical insights into how to achieve their goals.
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About CertNexus
CertNexus is a vendor-neutral certification body, providing emerging technology certifications and micro-credentials for Business, Data, Development, IT, and Security professionals. CertNexus’ mission is to assist in closing the emerging tech global skills gap while providing individuals with a path towards establishing rewarding careers in Artificial Intelligence (AI)/Machine Learning, Data Science, Data Ethics, Internet of Things, and Cybersecurity.
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