Why Should Organizations Today Allow Data to do the Marketing Identifying specific content that moves buyers down each stage of the sales funnel allows marketers to distinguish the efficient assets from the ineffective material
By Kousik Bhattacharya •
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Before the evolution of digital marketing, the marketing decisions and media planning were mostly dependent on 3 things - past performance, available media within the budget and decision maker's experience. With the concept of measurability and ROI, marketers have evolved to adopt more calculated strategies than assumptive plan.
From my experience, I have seen companies that changed their course of business and marketing after looking at data. As a result, they have excelled in their operations and became more profitable. These examples are very relevant in today's time when companies (mainly startups) are in a dilemma whether to acquire more customers or be profitable in the bottom line. I think both objectives can be achieved simultaneously, if the focus of the business is to create value rather than increase valuation. And taking data driven decision is the first step towards this achievement. We were able to grow Via.com into a 800 MN USD company at 35% CAGR with the consistent addition of positive numbers at the bottom line. This is achieved mainly because marketing strategies and business objectives are directed by data and statistics.
Let me explain some key benefits of the data driven approach -
Better Audience Insight:
Knowing your customer is the fundamental aspect of building any marketing strategy. Data tells you the demography, geography, affinity and in-market segments of different audience cluster to plan a precise communication strategy. Right message to the right people on the right medium is only possible when it is designed by data.
Enhance Funnel Efficiency:
Identifying specific content that moves buyers down each stage of the sales funnel allows marketers to distinguish the efficient assets from the ineffective material. This helps to optimize campaigns and product element that can lead to better conversion rate, and thereby positive ROI. For a marketer it is very essential to differentiate audience and campaigns based on the consumer position on upper funnel or lower funnel. Only data allows to do that efficiently.
Personalization and customer experience:
Big Data and advanced analytics have enhanced the ability to create highly targeted campaigns with personalized messages. Study shows that data driven automated campaigns targeting different consumers in the buying cycle improves the conversion rate by 8-10 times. In the digital world, buyers are impulsive, smart and have more options to choose from. So in this competitive market, hosting customers with right experience is the game changer. Collating the buyer's persona and pre-empting a tailor made campaign or site merchandising for the user converts him/her into a return and loyal consumer.
Predictive analysis and forecasting:
Different data sources provide valuable insights about the market forecast and helps in business prediction for the upcoming period. Strategies for product development, media buying, inventory management, demand supply chain system etc. depends on the various dataset and research.
Cross Selling & Up Selling:
An organization, today, cannot survive through pure "sales'. One has to explore newer avenues of escalating the revenue generated from a customer. That is what CRM and data driven marketing can ensure for an organization. The available data could expose those areas where the same products could be sold more frequently to existing customers. At Via.com, we provide customized and best-valued hotel and holiday deals to our existing customers, as we know their preferences and likings.
With all these benefits, data driven marketing is definitely a winning strategy for the organization. But the success of this strategy depends on the attitude of the organization as a whole. It is effective, when not only marketing strategists but other departments also consider the importance of data in decision-making.
