Understanding customer behaviour is a critical yet complex task. But with the right set of approach and perspective, any brand can leverage customer behaviour to drive increased sales, generate leads and ensure customer satisfaction throughout.
According to research by McKinsey, organisations that harness the power of customer behaviour data to generate behavioural insights, outperform competitive brands by 85 per cent in sales growth, and more than 25 per cent in gross margin.
What is Customer Behaviour?
Customer behaviour is the study of how customers and organisations prioritise, select, and purchase or invest in certain products or services of a company. It is mainly concerned with the psychological behaviour of a potential customer and how they interact with a brand throughout their buyer journey.
The study of customer behaviour includes:
- How customers think and feel about different options including brands, products, services, retailers, and sellers,
- The behaviour of consumers while researching and selecting a product or service
- How consumers are influenced by the surrounding environment such as peers, culture, and media
- How they reason and choose between different alternative options
- How marketing campaigns can be aligned with respect to consumers’ behaviours to drive increased sales
Factors such as customer-centricity, personalisation, and customer experience are what separates high-performing, world-leading brands such as Amazon, Netflix, and Google from others that are yet to leverage the power of customer behaviour.
Despite the strong impact of customer behaviour data, it is surprising to see how so many organisations are using a fraction of behavioural data available with them.
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You don’t need to be a tech giant or a large multinational firm to leverage the power of consumer behavioural data and analytics.
All you need is the right set of tools, knowledge, and a strong internal team that will help you shape a business model that has customer behaviour at its centre.
1. Deliver Personalised Customer Experience
One of the major agendas of customer behaviour tracking is to analyse different individuals and create a personalised customer experience that is suitable for preferences. Whereas with traditional marketing campaigns, marketers used to segment customers based on their demographics, age, gender, income, ethnicity, occupation, industry, or company size. For years, these marketing campaigns worked, but as brands realised that there’s more to customer engagement than segmentation, they started creating personalised experiences which showed significant impact.
Even customers began to realise that their journey with particular brands is changing, such as with Amazon and Netflix. In Amazon, the bar below each product you visit with the heading “Customers who bought this item also bought” or “X is frequently bought with Y” is a personalised recommendation that is based on multiple data sets created by your previous order history, wishlist, interests, brands that your browse most, or products that can actually deliver value to you..
Fueled by customer behaviour data, these organisations use advanced recommendation engine algorithms designed to serve customers dynamically personalised content and product suggestions based on each customer’s previous data.
Here are some quick facts that show how powerful customer recommendation algorithms are:
- 80 per cent of Netflix viewer activity is driven by recommendations that are personalised for each individual.
- Netflix’s recommendation engine saves the company an estimated USD one billion every year through increased customer retention and simultaneously decreased churn.
- 35 per cent of Amazon’s sales is generated by their recommendation engine.
2. Drive Customer Growth and Expansion
The modern customer journey is incredibly complex. The path to purchase initially involves multiple touchpoints spread over different channels, over an extended period, which can be days, weeks, months, or in some cases even years.
As per the Salesforce’s State of Marketing Report, 67 per cent of marketing leaders say that staying connected to a customer throughout their buying journey across all touchpoints and channels is crucial to the success of the overall marketing strategy.
Also Read: Expected Excellence – The Growing Demand for Personalisation
Here are three quick points for every marketer to use behavioural customer data for increased customer acquisition:
Clone your high-value customers
Target and acquire customers that show similar behaviours as your most profitable ones, and that is most likely to follow their path to purchase.
Invest in smart marketing bets with your acquisition budget
Focus more resources on potential customers and leads that are prospect buyers with the highest likelihood to purchase and provide the highest potential lifetime value. Stop wasting money on prospects that do not seem promising or are long-shots. Waiting for a lead to become a buyer in the next year is a complete waste of investment and efforts, especially with the fast-changing marketing tactics that are continually improvising.
Optimise the path to purchase via personalisation
Customers feel happier and privileged when a brand focuses on their personal needs instead of random promotions. Make sure that your messages and offers are aligned with your customers’ important decision drivers and help increase conversions by providing a complete customer experience that renders satisfaction and value.
3. Increase Customer Retention
Customer retention is a key differentiator for brands that impacts its sales and revenue. According to Esteban Kolsky’s research, 67 per cent of customers report bad experiences as a reason for looking for alternatives, but only 1 in 26 unhappy customers complained.
Of those non-complainers, 91 per cent leave the organisation and start engaging with other brands. For the 9 per cent that complain, companies often take long enough time to revert and solve the issue, which reduces customer satisfaction, ultimately driving the customers away.
You can’t rely on customer reviews or complaints to gauge customer experience, satisfaction, or to predict retention and churn. Not providing enough value to your customers through products or customer experience can be detrimental for your organisation’s reputation and decrease customer retention quotient.
Also Read: Is It Time We Stopped Talking About CRM?
How Netflix Uses Behavioural Data and Analytics to Reduce Customer Churn
Netflix is one of the most dominating players in the customer behavioural data and analytics segment. With over 148 million paid subscribers worldwide in f 2019, Netflix has successfully managed to leverage the power of behavioural data to deliver excellent customer experience.
It evaluates the amount of usage activity an individual customer needs each month to receive enough value to continue subscribing. If a customer’s monthly content consumption falls below the specified threshold, the customer retention rate further decreases.
By creating a behavioural segment for all customers that fall below the threshold for content consumption every month, Netflix can identify customers that are either on the brink of leaving the platform or are unsatisfied with their customer experience. With this, Netflix improvised and created several initiatives to engage their customers and deliver more valuable content.
It uses customer behaviour data to make recommendations that are suited to each viewer’s style, interests, previous watch history, genre etc. It even depends on behavioural analytics to determine what content to produce and license, which also helps them to prevent churn, as well as improve customer acquisition.
As a result of this, Netflix has been able to reduce its customer churn rate significantly. Executives estimate that the company saves around USD one billion a year merely by using behavioural customer data.
Also Read: Big Data, IoT, and AI Will Help Personalise Brand Experience
How to Collect Customer Behaviour Data?
Digital transformation has increased the number of touch points brands can have with their customers, which means there is a vast amount of information that is readily available about customer behaviour. And It can be captured via various methods:
- Sales data, traffic-generation source, interests or preferences shown by potential customers
- Through user-generated content such as peer recommendations and social media posts
- Data collected from customer-brand interactions such as customer service support, social community support, call recordings held on customer management systems.
The ideal place to start looking for customer analytics is the untapped consumer data that is present in the internal system of your company like customer purchase history and management information. Unstructured and external data such as verbatim comments or conversations, tweets, peer recommendations are often difficult to tap into and exploit successfully.
Analyse the insights driven from customer-based analytics and create skilled models for enhanced future performance and customer behaviour. Advanced data analytics techniques are highly capable of generating increasingly personal insights that can answer complex questions about individuals. It can evaluate the next probable purchase of consumers and even determine which product ad campaign would most likely engage them.
The ability to go beyond segmentation and minutely focus on individual customers rather than a member of a group is an incredibly powerful tool in understanding how customer behaviour works and how best we can influence them.
Insight-driven information helps organisations to make faster and more frequent decisions. It also improves financial performance, competitive positioning and effectiveness in executing marketing strategies.
Like Netflix, Google and Amazon, you can also leverage the power of behaviour customer data and increase your brand’s revenue, reputation and customer acquisition rate. Your customer’s behaviours can reveal valuable insights that can help you build marketing campaigns and strategies which can dramatically improve your B2C relationships and render a true customer experience.
Collect, analyse and implement your customers’ behavioural data model carefully and pay close attention to what is working out for your organisation.
