Big data and analytics: the next big thing in marketing

Of the many similarities between Big Data and a Marketer, one thing stands out: both have an insatiable appetite for information. If you don’t know what is broken, you won’t be able to fix it.

In an era where the cliché “ Change is the only constant” is relevant more than ever, people are looking at Analytics to make their decisions more data driven. Analytics is evolving into a necessity for business not just to analyze and predict future outcomes but also to create and shape them. It is slowly becoming the oxygen for a company and the company’s survival on the long run might depend on its effectiveness in using big data.

Humans are not the best at expressing their needs. Some human needs are so latent that people don’t even realize their existence. Thankfully, we no longer have to rely only on questionnaires and interviews for data collection. Collecting customers’ preferences through their online behavioral pattern and analyzing them can provide much better results. This can be used to take the level of customization a customer experiences to a whole new level.

Analytics provides insights into the decision journey of an individual before buying a product. The marketing team can identify the key features in the product that attract the customers. It is also indispensable in understanding the local markets and helps in coming up with marketing strategies at regional levels.

Customers nowadays don’t want products pushed to them and would rather prefer buying stuff at their convenience. Thus, it has become necessary that a high degree of customization and accuracy is required while marketing products to customers. Whether a person is your customer or not may depend on that first product you recommend to him.

Equally important is the appropriate pricing of the product. Big Data analytics can help in determining the ideal price of the product. It can also provide insights into the possibility of differentiated pricing of products based on the customer’s willingness to pay.

Big Data can be used to leverage the Next Best Alternative (NBA) marketing approach. This is a customer centric approach wherein unique, real-time promotional offers for a customer are considered and the optimal one is determined. This is radically different from the traditional approach of creating offers for the product first and then attempting to prospect.

Analytics can also help in brand management by analyzing customer reviews / comments over a period of time. This is one of the best ways to identify customer’s expectation from the product. The reason for any sharp change in the level of overall satisfaction must be analyzed. Tangentially, it can also be used to identify new potential markets and facilitate product diversification.

A Forrester reveals that big data and analytics is being used by 44% of B2C marketers to improve responsiveness and that 36% actively use analytics and data mining for better forecasting. Given how young the field of big data is, these are astounding figures.

Data, which were once qualitative (Weight – Slim, Fit, Fat) have become quantitative (kgs, lbs) with the advancement in technology (invention of the weighing machine). We are on a similar transitional phase in the way we market and sell goods. Analytics provides a way of quantifying marketing decision, which can come in handy while recording, organizing, justifying and learning from our previous decisions. Some of the ways in which we can augment our marketing decisions with analytics are listed below.

A research conducted by B2B Leads concludes that a salesperson spends 50% of his time in unproductive prospecting. Big Data Analytics can arrive at leads accurately by identifying people who actively search for a product. These leads can then be acted upon by the sales team.

The sales force can also use analytics to improve on the logistics front. Historical trends may be used as a predictor of demand and for stocking up the inventory. An earlier than expected delivery would greatly improve customer satisfaction and go a long way in customer retention.

By delegating identification of potential customers to analytics, sales representatives have more time to spend on building customer relationship, retaining customers, customer engagement and after-sales service.

Customers prefer personalized marketing communication. Salesforce estimates that 65% of buyers from the B2B category would choose to switch brands if treated generically. Analytics can help the sales team engage with the customers better, with personalized suggestions and offers.

With wearable devices and IoT gaining momentum, pharmaceuticals, fitness brands, sporting brands and lifestyle stores can analyze their customers’ behavior and come up with suggestions. Analysis of data from these devices would take personalization to a whole new level.

Analytics can be employed to identify how products reach the customers. This helps the marketing team in zeroing down on the distribution channels that attract the customers more. This also helps them in identifying and mitigating the problem of counterfeit products in the market.

CIO insights reports that 85% of organizations have trouble in accurately predicting sales as seen from the figure below. Better sales forecasting using big data and analytics will lead to realistic target setting. This enables preparation of a better financial budget and gives the top management and the sales team, a better overview of what to expect.

Predictive analytics has also brought about disruption in the job market. Analytical skills and tools are becoming necessary to run business and hence the marketing team must be equipped with knowledge of the same. In view of these changes, here are a few things that marketing leaders can do to build a big data and analytics centric marketing team:

With AI and machine learning along with predictive analytics gaining momentum, marketing leaders must focus on change management to accommodate these technologies in their organization. Though it seems overwhelming at first to delegate organization wide important decision to big data and analytics, leaders must also consider its long term impact. Trial runs before implementing organization-wide changes might help.

With automation becoming a part of many jobs, most jobs would require redesigned roles. Hence, the skill matrix of the organization needs to be updated.

Marketing leaders must also build a culture of analytics driven decision making in the organization.

The best thing about Data Analytics is that it is helpful for organizations of all scales. For most smaller organizations, investment on predictive analytics holds the key for rapid expansion. Large, established organizations also use analytics to understand trends in the market.

Though several technologies have sprung up in the past before becoming irrelevant, predictive analytics doesn’t seem like yet another one of those. Judging by how essential it has become to all scales of business, predictive analytics is here to stay for a very long time! Investing on them and building an organization centered around analytics would be a wise decision.