5 Ways to Understand Consumer Behaviour Through Data-Driven Marketing

graphic of smartphone with white screen and paper
graphic of smartphone with white screen and paper

Once upon a time, marketing experts relied on past experience and their own intuition in order to understand the customer and their buyer behaviour. By using ex-post methods, such as focus groups and polls, marketers would use the insights gathered from these methods to build an image of their customer and crunch limited available data to try to envisage how their product will position itself firmly against their competition. However, this has changed immensely with services such as Facebook, Amazon and Netflix coming into the fold and showing us first-hand how data-driven marketing doesn't just help us understand the consumer but it helps drive consumer behaviour and substantially increase gains.

image of an ipad with the netflix app open next to a bowl of popcorn

According to research done by market research firm Invespcro, marketing firms that exceed their revenue goals apply personalization methods 83% of the time. To add to this, businesses that use data-driven personalisation methods recorded between five and eight times the return on investment (ROI) on their marketing budgets.

So, what does this all mean? It might be time for you to consider using data-driven marketing in your own business to get a better sense of your customers and their buyer behaviour. Here are 5 ways to better understand consumer behaviour, with insights into the techniques that marketing pros can use to effectively deliver their message to the right audience.

Table of Contents

Consumer Behaviour definition

Consumer behaviour is the study of consumers and the processes they use to choose, consume, and dispose products and services. These processes include the consumer's emotional, mental, and behavioural responses.

Consumer Behaviour models

While HubSpot delves deeper into 6 consumer behaviour models, here is a quick overview of them:

  • Traditional Behaviour Model: understanding what consumers purchase based on their wants, needs, and emotions. 
  • Psychoanalytic Model: understanding that consumers have deep-rooted motives, both conscious and unconscious, that drive them to make a purchase, motivated by hidden fears, suppressed desires, or personal longings.
  • Sociological Model: understanding that purchases are influenced by a consumer's place within different societal groups such as family members, friends, and work colleagues.
  • Contemporary Model: understanding how buyer behaviour focus on rational and deliberate decision making rather than emotions or unconscious desires.
  • Black Box Model: understanding that consumers are individual thinkers that process internal and external stimuli in order to make a purchasing decision. 
  • Hawkins Stern Impulse Buying: understanding that purchases aren’t always a result of rational thinking but more of an impulse.

Consumer behavioural analysis

Consumer behavioural analysis isn't always easy but it does get easier, the more time you take to learn how consumers make purchasing decisions for a product or service. Analysing consumer behaviour allows you to really dive deeper into behavioural patterns and buyer behaviour, and a good place to start would be to ask yourself a few questions like:

  • Who influences a consumer's decision to purchase the products? 
  • Why is the consumer buying this particular product or service?
  • Does a consumer prefer one brand over another, and if so, why?

Consumer behaviour analysis plays an important role for marketers and how they communicate products and services to its consumers. You'll get the necessary information you need to understand the motivations behind certain behavioural patterns. 

Behavioural segmentation definition

Jon Miller once said that "Knowing who your customers are is great, but knowing how they behave is even better." Traditional methods to segmentation focused on who the consumers are and segments were based on demographical information like gender and age. Now, however, consumer behaviour is one piece of the puzzle; behavioural segmentation is the other. 

Behavioural segmentation is understanding consumers not only by who they are, but by what they do (their behaviours), using insights from consumers' behavioural patterns. This helps brands to segment their consumers into groups according to how they might respond to a product or service. 

The importance of Consumer Behaviour Theory

If you are trying to understand what goes on in your consumer’s mind when it comes to making a purchasing decision, you aren't alone. No amount of guesswork will accurately tell you this, which is where the theory of consumer behaviour comes into play.

This theory is the study of how people make decisions when they buy products or services. This can help businesses and marketers better understand these buyer behaviours, and leverage them to predict the patterns a consumer will make before purchasing. Consumer Behaviour Theory also helps identify what factors influence these buying decisions, which can provide businesses and marketers with insight into the strategies they need to influence this behaviour.

4 factors that influence buying behaviour

1. Psychological Factors

Psychology can play a big role in determining of consumer behaviour. While psychological factors, such as attitude, motivation, personality and beliefs, may not be easy to tangibly measure, they have power in influencing purchasing decisions.

For example, a person who believes in or is motivated by family will have different buyer behaviours than a person who is motivated by being independent, or someone whose lifestyle is based on a healthy belief system may buy organic health foods instead of fast food.

2. Personal Factors

Personal factors are what just that - personal to the consumer, and so will vary from person to person, which may produce different consumer behaviours. Personal factors include age, gender, occupation, background and culture.

For example, "Boomers" will buy differently than Generation Z, and a person whose culture prohibits certain food will buy differently to another culture

3. Social Factors

Because humans beings are social beings, and are often interact with the people around them, this can influence their buying behaviour. Social factors that influence this behaviour include a person’s friends, family, physical community, work or school community.

For example, a person who finds themselves within a school community will have different purchasing habits than a person in a work community.

4. Economic Factors

One's economic situation also impacts buying behaviour. When a country or market is thriving, the economy is positive and leads to positive money supply, giving customers more purchasing power. On the other hand, a weak economy can indicate a struggling market and less buying behaviour. Factors such as personal income, family income and credit can all influence consumer behaviour.

For example, when a personal has more disposable or family income, their buying power increases, and both basic items and luxury items can be purchased.

5 Ways to Understand Consumer Behaviour Through Data-Driven Marketing

1. Apply available data to your marketing efforts

There is no doubt that marketing has been revolutionized by data analytics. On an everyday basis, more data is being produced and made available. Think about the number of clicks you make when you're online window shopping, or the location pinpoints your smartphone can pick up when searching for "restaurants near me". From the many card transactions made every minute to the hours of video content consumed on YouTube, this is all data.

There has never been a time before now where more data was available for analysis. If we just take a look at our time spent online, mobile users in the Philippines take the lead spending up to 10 hours a day in front of their screens. It’s easier than ever for marketers to follow digital bread crumbs to gather and analyse data on consumer behaviour, which will influence the marketing strategies for their chosen niche.

lots of people crossing the road

It goes without saying that converting the data you gather into actionable insight requires a combination of data analytics and communicating the resulting insights into actionable steps that will influence consumer behaviour.  The much-lauded leader in this field in the past couple of years has been Lenovo. According to them, they managed to develop a predictive model which helps them assert if a visitor to their website is going to buy one of their devices in a matter of seconds. By using this data, they carefully position customised content for the visitor with an accuracy of almost 90%.

2. Base your marketing strategy on scientific analysis

Even though the times have changed, the founding principle of a data-driven marketing strategy is still a very old one – understand your consumer and their needs. There’s still no definitive answer on how to predict consumer behaviour. The rule of the thumb, however, is finding data which can be analysed and segmented, and thereafter expanded upon. For that reason, there are essentially three steps that need to be taken for a proper analysis to be conducted.

open laptop on a desk with data analytics on the screen

Consumer research:

The first condition is to understand your customer demographics, their interests, search analytics and how all these can be merged into forecasting consumer decisions. Using the Audiense tool provided by Meltwater, brands can search for keywords and terms to establish a consumer group that engages with that topic the most. Breaking it down by factors such as gender, age group and related interests marketers gain data-driven insights into who the audience is and an understanding of their behaviour as well as psychology looking into personality type and values. 

Segmentation:

As part of planning for your marketing campaigns, every marketer needs to know who they are targeting. One method of segmenting target market is the use of demographic data. This includes the use of data relating to the consumer research you did, as mentioned above. With this information, it’s important to divide your customer base into segments and prioritise target audiences who have the most interest in your field, particularly customers with intent to buy. Using the Audiense tool, you receive analytics on consumer behaviour and traits based on a specific discussion point related to your brand. This can then help influence marketing and advertising decisions. 

screenshot of Meltwater Audiense tool

Third-party data:

In order to have a complete overview of your market, competition analysis is essential. Add to that the analysis of consumer behaviour online and a company can be said to be prepared for connecting with and understanding their target audience properly.

Data-driven marketing is thus grounded in creating the image of the perfect consumer based on real people being analysed, thus focusing on influencing their decision-making process and attempting to predict their buyer behaviour over time.

3. Implement a data-driven marketing strategy

Once you have your analytics on consumer behaviour, the question that is naturally posed is – how can you actually predict anything?

We all buy certain items at certain times in our lives, the so-called life stage based purchases. Every time we buy a new car or a home, marketers can use this information to predict complementary purchases. By using these analytics effectively, they can target consumers by creating helpful content marketing such as articles or recommendations to increase sales.

person pinning a black thread on white and blue paper on a board

This still might seem like some kind of dark art, but it is actually entirely based on what we do. Even though it is not possible to look for “people who just bought a new car”, it is possible to analyse existing databases to see people who have, at some point, bought a product and backtrack the buyer behaviour and motivation that led to the purchase. By correlating this data with consumer demographics such as age, gender and income, it becomes easier to segment the market and find connections, consequently making much more successful predictions on your consumer's behaviour and purchasing decisions for the future.

4. Remember, interest and intent are not the same

This is the trickiest part of data-driven marketing. It’s much easier to understand consumer behaviour and interests of target demographics than the intent to buy. It is far different to just know that someone will buy something than knowing when that person is going shopping

This is where connecting databases is essential for marketers to devise a strategy. If a company is able to create a data partnership and gather information on shoppers from other websites and services, it will have an easier time measuring consumers’ intent. The universal wisdom here is as follows – if a person is looking at articles about cars, we can safely assume that the person is interested in cars. But, if that same person clicks on product pages of an actual used and new car lots, this is a much better indicator of intent to buy.

5. It can do wonders for any business, anywhere

If you have a system set up, the information derived from it about your customers and their habits is a virtual El Dorado, limited only by your imagination and the skills of your data scientist. For example, a company with a telephone answering service which can correlate their customer insight at the door, so to speak, can achieve an incredible boost to their business.

Remember that consumer behaviour is evolving all the time. Your business needs to understand its customers to effectively target them when they are ready to make a purchase. If, for example, there is a customer who begins their purchasing journey by visiting a physical store, this is going to be useful information that you need to know. Once at the store, the customer looks at what products are available and does further research in their own time. This could be looking at other customer reviews or getting feedback from people who have used these products before. Then ultimately, the same customer makes a decision and purchases one of your products online. Or the reverse could happen, where they see your products online and make the purchase in store. The customer journey may look a little different but as a business, how can you effectively ensure that this customer actually makes a purchase from your business? The answer lies in understanding that having information about your customers, and their consumer behaviour will undoubtedly work in your favour.

The implications are endless, whether they are connected with empowering your sales department by giving them hot points which will result in a buy or your R&D by giving them insights into what your customers expect from your product.

Data harvesting is the new way of doing business, period. If you would like to learn how to use data to drive your marketing campaigns, fill in the form below and the Meltwater Team will reach out.

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