This week we focus on the role that Data Science and Consumer Psychology has played in the past few years to redefine and rebrand Digital Marketing.
This blog is the first part of the two-part seriesfocusing on: How Data Science and Consumer Psychology have structured and paved a new way for Digital Marketing.
What connects Data Science and Psychology?
There is a strong belief that Psychology and data science are closely tied together. How people perceive data or results of an analysis is entirely rooted in aspects of human psychology and the understanding of human cognition and how people process information.
Additionally, this also drives how the results of a data science project are presented to others in terms of colour usage, the flow of patterns, context and even culturally (for example, in some countries, people read back to front, bottom to top, or right to left).
It is further argued that human psychology’s aspects drive the choice of data analysis tools and which questions to ask of the data.
As digital marketing data is created by people engaging with content, the wide variety of attributes and behaviours embedded within the information is an exciting treasure to discover.
Overall, the main thing that ties these two domains together is the heavy statistics element. Both involve a vital aspect of statistical knowledge as a means to generate robust insights from data.
One critical maneuver of data science understands why people behave the way they do, i.e. behavioural economics (and/or psychology). This is apparent in subdomains such as natural language processing, computer vision etc. It’s also blatantly implemented in recommendation systems, e.g. Netflix, Amazon etc.
One thing that sets digital marketing apart from traditional marketing is its ability to track and monitor real-time marketing results. In other words, data availability. Having access to live data allows you to spot market opportunities, save precious company resources, and garner more profit.
But this does not happen automatically.
The secret to emerging on top of the congested online world is data science.
But before we delve deep into the sea of data science, let’s get some clarity on the concepts.
What Data Science Is and Is Not?
There is a lot of confusion about what data science is and is not.
Specifically, people often interchange the terms of data science and data analytics. The easiest way to differentiate between the two is that data science predicts the future, while a data analysis looks to summarize the past.
A Data scientist makes predictive models using regression, machine learning, and other advanced statistical methods, while a data analyst uses descriptive statistics to analyze past patterns.
The existence of Digital Marketing strategies would be non-apparent without the presence of data science. All information collected to identify your customer’s needs and preferences help you tailor your campaigns according to your customer’s wishes and spending habits.
Data science uses artificial intelligence and mathematical modelling to unlock a new set of insights and answer questions such as:
Who are your most promising customers?
What choice alternatives do consumers of your product have?
How do people feel about your brand?
What other products do your customers want to buy?
A marketing team can eliminate waste and target customers in cost-effective and personalized ways by leveraging data science.
Concepts Under The Data Science Umbrella
Here is a quick overview of some data science concepts and how they relate to each other to avoid confusion with the terminologies.
Big Data: Big Data is a huge data set (from several sources) that is too complex for traditional applications to process.
Data Mining: This is the process of analyzing large data sets to predict outcomes. Methodologies include descriptive modelling, predictive modelling, and prescriptive modelling.
Machine Learning: This concept is defined as a process that uses artificial intelligence to learn and make predictions on the data that it is working on. It is used in data mining.
Data Analytics: It is the process of inspecting a defined data set to draw conclusions and discover patterns from the analyzed data set.
Business Intelligence: Business intelligence is defined as strategies and technologies that transform raw data into meaningful and useful information to enable more effective, tactical and operational decision-making.
How can Data Science aid your Digital Marketing efforts?
Data science methods like machine learning, clustering, and regression have moved marketing from a creative domain to a scientific one. By leveraging data science, marketing teams can extend their top-funnel approach to a full-funnel one and uncover product and customer insights at scale unprecedentedly. To do this, growth marketers and businesses should understand what data science can do.
List of benefits of implementing data science in digital marketing:
One of the essential elements in digital marketing is knowing your target audience. Businesses often use a Customer Relationship Management (CRM) software to achieve this. This software consolidates information from your company’s various departments (marketing, sales, and support) to develop a comprehensive overview of your customers’.
Applying data science to it can help marketer gain valuable insights such as:
Who are your most valuable consumers? This will help you to target a lookalike audience in your future campaigns.
Why did your customers choose you? Keep doing what is delighting your customers.
How did they find you? So that you can place more effort and funds on these channels
Why did some clients terminate your service? Identify deal breakers and avoid them.
When you have a total understanding of what your consumers need and want, you will be in a better position to implement more relevant promotions and content for your audience. These insights let you know what you need to do to retain their business.
2. Optimizing Marketing Campaigns
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Past campaign data can be used with data science to plan and better execute your next marketing campaign. Anchor your strategy on empirical data rather than assumptions and guesswork to significantly reduce the chances of getting poor results.
Some insights your past campaigns can inform you of are:
Which creatives sparked the most interest from your fans? Similarly, design your next creatives.
What was the time that your potential clients were mostly online? Share your content during those timeslots to get higher engagement.
Which channels gave you the best conversion rates? Invest more resources in those channels.
How were the engagement and click-through-rate of your marketing campaigns? Review your audience set and ensure the right people are being targeted for your advertisements.
Data science can make or break your marketing campaigns. While it does not assure success, it increases the likelihood of it.
Plan your campaigns according to your business needs, budget, customer behaviour, and data extracted from the mentioned sites. In other words, give them the content they need at the right time and place.
3. Building a Data-Driven Content Marketing Strategy
Data science can also help you to create the RIGHT content – relevant content that will build a connection between your audience and you. Analyze all the content that you have created. What was popular, and what didn’t work? These insights will shed light on the topics that resonate the most with your audiences.
Here are more examples of how data science can furnish your content strategy:
Create the content on trending topics: Use free tools like Buzzsumo to identify trending topics for a core keyword and Ubersuggest to find out the keyword’s search volume. Select those topics with the potential of going viral and share valuable insights on them.
Opinion mining: Defined as identifying the emotions behind a body of text, opinion mining can reveal your customer’s sentiments towards you and your content. This allows you to take proactive measures to rectify any impending issues.
4. Channel and Budget Optimization
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In 2020 more than ever, businesses need to operate through multiple channels, namely, website, email, social media and events. This is why optimizing all these channels to get the best return on investment is an add on task for businesses.
Data science helps you to see and compare the success and the issues with previous campaigns, the percentage of the people engaged and their behaviour on each of your channels.
Although your performance will vary from one medium to another, the key is to analyze and to test, which works better at a certain point in time.
What’s more, traffic data analysis will help you see what amount of money you need for which channel, so consider budget optimization once you determine which channels you want to focus on. You can then enhance customer acquisition rates and develop a more profitable campaign for your business.
5. Real-Time Data Aligned to Customers
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Businesses/Marketers usually collect the data about the customers in bulk after every campaign to track its progress. This changes with the implementation of Data science in digital marketing. The current or future digital marketing campaigns can be designed as per real-time data, focused on current market patterns and consumer trends rather than analyzing previous campaigns’ behaviours and performance and minimizing recent historical data involvement.
Data science changes the paradigm of current digital marketing altogether; the current data science techniques fetch data about the market trends, the effectiveness of execution time, and consumer behaviour and purchasing trends. This proves particularly essential when exploring new opportunities, forecast trends, and beating competitors. Moreover, a loyal customer base can be effectively targeted at the right time with strategically designed marketing content.
6. Increasing Customer Experience and Customer Retention
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High-quality customer experience and a satisfied consumer base are arguably the utmost need for your business. You want a fan base, people who love to talk about you and increase your net promoter score. With Data science, you can efficiently implement marketing campaigns that help you understand why, when, and how of consumer behaviour.
You can strategize and deliver a real personalized experience, leaving your customer to feel special while buying your product or being a part of your online community. You can witness an increase in customer retention while reaping the rewards of your strategy.
The Road Ahead
Every digital marketer has access to tons of data. But having data does not equate to better marketing. It is how you use this data that will determine whether you succeed. It’s time to grow from “We think” to “We know” and reach your target customers before your competitors do.
Point is simple
People like to be pleased. Luckily, data science gathers information about your customers and gives you the guidelines on how to craft your next marketing campaign.
And before you go –
Come back next week for the second part of this blog, where we focus on Consumer Psychology and how it influences Digital Marketing.