How Does Data Analytics Play a Role in Marketing?

With every tap we make on our smartphones, every click we make on our PCs or GPS, or search queries on any other device, we generate a tremendous amount of data around the world. With the right analytical software, we can sort this surge of data into organized and actionable insights. These data analytics are insights used in various industries all over the world. Throughout the last decade, organizations have been conducting and planning their marketing strategies in an innovative way with the help of data analytics. This allows brands to send more structured and targeted messages to receive a larger return on their investment, or ROI.

What is Data Analytics?

Data Analytics is the process of examining data to discover important information and trends that can be used to draw conclusions for business decisions. Understanding data allows businesses and organizations to optimize performance and maximize profit through data-guided decision making.

What are Types of Data that Marketing Teams use?

Types of data in marketing include:

Customer Data: This type of data allows businesses to better understand and target advertising to their consumers. By analysing customer information, such as  purchase histories, locations and online behaviour, businesses can better identify buyer’s needs and expectations.

Operational Data: This type of data considers the daily, logistical processes of operating a business, revealing opportunities to improve procedures and expand operational efficiencies.

Financial Data: Understanding the financial data of a business includes budgets, margins, advertising costs and pricing which leads to greater operational efficiencies and profitability.

Analysis of different types of data in marketing grants businesses optimal insights into their operations and grants opportunity to improve to meet the needs of the consumer.

What is the role of Data Analytics in Marketing?

Businesses today have more access to information about their customers. Surface-level data such as the age of their customers, their gender, geographical location, etc. is being used by companies for detailed insights regarding customer behavior. Customers are increasingly looking for services and products that personalize an experience. This marketing strategy is implemented to make customers feel that they are valued by the brand as unique people and not just a lead on a spreadsheet.

What is and what is not an effective data analytics strategy?

One of the many advantages of data-driven marketing is the greater visibility it offers to brands, and it is entirely possible with the help of analytics in market research. Before digital marketing and all its related data became the trend, marketing teams found it immensely challenging to understand which of their efforts were working and what needed to be changed—factors which contribute significantly towards making a purchase. It was almost impossible to figure out if a promotional campaign increased sales or if it only created brand awareness. With the help of data, marketers can now track the journeys of their customers, from initial interest to final purchase. Insights are driven today with the help of CTRs, or click-through rates, as well as website cookies, which allow marketers to have extremely clear visions of what is working out for a brand and what isn’t, helping them to prioritize allocating their expenditure to the right channels.

Data scientists are as important as the data itself

Data is simply a set of numbers, and it is only through structured analysis that such data can be read and transformed into valuable insights that are tremendously useful to companies. And while software packages offering analytics are of incredible value, they do not negate the need and usefulness of experts and highly skilled data scientists. While technology can help process large quantities of data and numbers within a fraction of a second, data scientists are really needed for the development of effective objectives and marketing strategies derived from available data studies.

Understanding your customers as people

Regardless of how much an organization interacts with its customers, there is only a certain degree to which data can be collected from them first-hand. Customers are not linear characters. They, like any human being, have multiple facets to themselves, all of which play a role in picking a brand. For the same reason, brands are now augmenting their first-party data with third-party sources. Even if it comes with its own challenges, like the reliability of third-party data.

Full-funnel approach to marketing

The full-funnel marketing approach is quite worn out and needs some tweaking in this rising world of social media. Consumers no longer maintain a standard, linear journey with brands where they simply pick a product and make a purchase. Instead, more customers today conduct their research independently, from corporate sites to social media websites. Social media, in particular, is an extremely important part of the marketing funnel in modern times. 43% of users between the ages of 17 and 25 are using social media to conduct product research and make purchase decisions. Marketers need to be able to target this group and build a relationship with potential customers in order to truly use a full-funnel marketing strategy.

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