Marketing

Marketing and customer analytics: Taking growth to the next level

Being aware of your customers’ requirements and deploying the right marketing strategies to
complement these requirements are crucial for business growth. But in today’s rapidly
evolving market, the importance of measuring KPIs and getting a holistic view of the market
has increased exponentially. Thankfully, we can leverage the power of marketing and
customer analytics to stay on top of the competition.

What is marketing analytics?

In simple terms, marketing analytics is defined as using technology to glean market-related
data. The digital activity of consumers generates a plethora of information, which companies
can channel into measuring various key performance indicators (KPIs) and boosting sales.

Marketing and customer analytics functions

Any online activity leaves a digital footprint. Customers using a product or a service generate
data through multiple touchpoints such as websites, social interactions, payment gateways, or
sales funnels. Customer-generated data is broadly categorised into four types.

Behavioural data

Web behavioural data includes all the actions visitors take on a website, such as tapping, typing,
scrolling, or swiping. For instance, factors such as how long they stay on a page, what pages they
scroll, which pages they click on, and what are the commonly searched sections can be identified
and quantified by digital analytics and used to improve customer engagement.

Transaction data

Customers generate a lot of data while transacting online. It includes the pattern, date and time of
purchase, and product or service costs. This type of data provides huge insights into customer
preferences.

Product or service usage data

This data tracks the online involvement of customers with a product or a service. For instance, if the
product is a healthcare app, customer analytics will track its use frequency, popular features, and in-
app purchase levels. Product usage metrics provide real-time insights into how customers view the
product or the service.

Text data

Customer-generated reviews, testimonials, comments, and ratings are first-hand evidence of
how customers actually feel about the product. This data can build trust and credibility about
the brand among its customer base.

Why does digital intelligence matter in your business?

Just over two decades ago, consumers gleaned information about the products and services
they needed from print media or television commercials. Advertising was a unidirectional
affair. Customers’ proximity — or the lack thereof — to brick-and-mortar stores further
limited the choice.

In the new millennium, e-commerce sites and interactive media have completely transformed how
people shop and businesses run. eCommerce was already on the upswing with the advent of digital
media. But in the wake of the COVID-19 pandemic, people are buying even essentials items online.
Businesses that have kept pace with this radical transformation are flourishing. Even businesses that
operated from physical establishments have begun building a strong online presence to stay
relevant.

COVID-19, hopefully, is behind us. But the shift in consumer behaviour has outlasted the pandemic.
The fact that buying patterns have changed irrevocably is an eye-opener. It means that businesses
that have leveraged deep domain knowledge to engage with and influence their customers at a
granular level can thrive in the new normal. To understand why customer analytics is essential, we
must first understand basic business models.

Types of business models

Each business has unique challenges and a distinctive target audience, and therefore, different
marketing strategies. At a primary level, your business model determines your strategy. If you cater
to large companies, you might want to use CRMs to reach out to them. If you serve individual
consumers, you might advertise on e-commerce apps. Broadly speaking, there are four types of
business models.

B2B

B2B is the business-to-business model, where one company sells goods or services to
another. Manufacturers of industrial materials, car parts, or facilities management companies
are examples of B2B model.

B2C

B2C is the business-to-consumer model, where a company targets individual consumers.
Restaurants, healthcare centres, and online entertainment platforms such as Netflix typically
work on the B2C model.

C2B

In C2B or the consumer-to-business model, the consumer provides goods or services to the
company. Affiliate marketing is an example of the C2B model, where bloggers backlink a company’s
product on their website and reap financial benefits in the process.

C2C

C2C implies consumer-to-consumer transactions, where consumers trade directly with co-consumers
by listing their products or services on a shared platform such as eBay or Amazon Marketplace.

Good marketing aims to acquire, engage, and retain clients, as well as generate revenue for
suppliers. But basic marketing is not enough to meet demand anymore. Entrepreneurs need to
deploy analytics to understand, predict, and even drive trends in the market.

Marketing and customer analytics spell success

Analytics services collect extensive data on how user traffic flows through the business
website or the app. This gives companies full visibility on consumer behaviour. There are
predominantly four types of data analytics.

Descriptive

Descriptive analytics gives an insight into past customer behaviour. It reveals how customers
received a certain product or reacted to a certain situation, which helps businesses strategise better
for the future.

Diagnostic

Diagnostic analytics tries to comprehend the reasons for certain customer
behaviours. This can aid businesses in building better products, targeting the
right audience at the right place and time, and not repeating past mistakes.

Predictive

Predictive analytics uses data to identify patterns in customer behaviour and
predict future trends. With this data, companies can foresee both risks and
opportunities in their domain.

Prescriptive

Prescriptive analytics suggests the best way to address customer behaviour and
provides insights about optimal ways to address any circumstance.

When taken together, analytical data provides a holistic view of the customers and the
market at large. It helps businesses strategise better, build better products, and
optimise their offerings. With customer analytics, it is possible for businesses to plan
market segmentation and hyper-target niche audiences, eventually driving more
conversions. Businesses can deploy customer analytics to build brand value and
improve their brand positioning. Tracking and analysing data also enable them to
personalise the content and the product.

With predictive analytics, it is possible to anticipate future consumer needs.
Businesses can plan and build a new line of products and services — ones that
their customers are not even aware that they need. It is also possible for
businesses to switch to more profitable segments and influence loyal customers
and move to higher tiers.

Bottomline

With the world at their fingertips, consumers today are more connected,
discerning, knowledgeable, and influential than ever before. In many ways, they
are the real drivers of commercial success. And therefore, businesses
need analytics services to know what really drives consumer actions.

To some extent, traditional marketing methods such as TV commercials and print ads
are still relevant. However, they are more about creating brand awareness and reaching
a mass audience. With more and more businesses now aiming at differentiation and
seeking niche audiences, hyper-targeting through social media platforms is clearly the
need of the day.

By applying digital analytics to customer-related data, companies can fine-tune their
marketing strategies, hyper-target specific audiences, customise their products,
increase engagement, and optimise sales. Integrating AI into your marketing game plan
is no longer a differentiating factor — it is a marketing essential.

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