Gone are the days when marketing decisions were guided by intuition and experience. Important marketing decisions are now determined by big data. This refers to the study and application of big, complex datasets, which cannot be processed by traditional data-processing applications. These figures generate insights that can lead to better business decisions and strategic moves. The application of the right technology improves the quality of decision making and detailing processes.
As the number of outputs and customer characteristics have increased, companies are faced with huge volumes of both structured and unstructured data. This level of processing is beyond the capacity of traditional databases and software techniques.
I use Google Analytics extensively in my work and also have my hands on a couple of big data tools. Digital marketing is my area of expertise, so I know where businesses can start when using big data in digital marketing. In this article, you will learn three examples of how big data can be leveraged for digital marketing success.
Designing Better Marketing Campaigns
Big data enables companies to better target the core needs of customers by developing rich and informative content. Let’s understand how it helps companies collect data about customer behaviors. One example is cookie files. They collect information about customers’ activities as they browse the internet, generating personalized data in the process.
Campaigns that use big data are more effective than aggregative advertising used in the past. The good thing about using big data for creating marketing campaigns is that it takes the guesswork out of determining what customers want. Marketers can develop different buyer personas using data like customer behavior, purchasing patterns, favorites and background. For example, they may find that women are more likely to respond to email campaigns, use coupons and engage in bargains and deals, and shape their digital marketing campaign from there.
Though applying big data to digital marketing is a great idea, it’s necessary to use good analytical tools to ensure the data presents valuable conclusions. These methods ensure that actionable insight is derived in an efficient manner so that companies can make their decisions without delays. To evaluate what makes a good analytical tool, it should be able to access all types of data including cloud, social media data, log files, websites, emails and other unstructured data. It should support campaign attribution tracking, real-time analytics, funnels and third-party testing and integration tools.
Making Better Pricing Decisions
Traditionally, companies price products and services using basic information like product cost, competitor pricing, perceived value of the product from the customer and demand. With big data, you can use many other factors to make pricing decisions. For example, you can use data from completed deals, incentives and performance-based data. Big data emphasizes making pricing decisions as granular as possible, particularly in the business-to-business (B2B) sector, as each deal is different from the next.
When using big data for price setting, companies need to remember that they may already have plenty of unused data at their disposal, such as customer preferences and general economic information. The challenge is how to derive valuable insight from this information. For example, does your pricing strategy consider what products a particular customer has purchased over the last five years? What is their disposable income? How much can they afford to pay for a product? Additionally, does your pricing strategy consider macroeconomic indicators like quarterly GDP growth rate, inflation rate, exchange rate, interest rate and government spending of the countries you operate in? Incorporating these insights will lead to better pricing decisions.
Big data also allows you to automate, which can save time in price settings and lead to more accurate pricing decisions because there will be no human assistance and hence less chance for error.
Showing Appropriate Web Content
Online marketers will be able to serve customized content to their website visitors by tapping into their knowledge base to determine which content will be more engaging to each visitor. Netflix does an exceptional job providing visitors with individualized recommendations based on the movies and shows they have watched. You can apply the same concept when designing your website by refraining from thinking of your page as a static site. For example, look at “time spent on page” data to determine what the visitor is interested in; the next time that particular visitor comes to your website, you can show them relevant content based on their browsing history.
Just as search engines return different results when you search for a term in different locations, your website will look different depending on who is looking at it. Though it will be a technical challenge to show customized content, an increasing number of consumers are demanding personalized experiences. Digital marketing teams that can’t meet these demands will not help their organizations compete in today’s market.
Build your personalization strategy by using deductive research, inductive research and customer self-selected methods. Ultimately, the consumer will decide where to click and what to purchase, and companies that can serve those consumers better will win the game. It will be the early adopters who win the race because they have an initial lead.
Big data has gained considerable attention as an effective tool for digital marketers to gain insight into what their customers need and want. The capacity to process large datasets is far more complex and advanced compared to traditional systems. Unlike early adopters, not all organizations have integrated big data into their marketing strategies. Those companies that haven’t already started will have to evaluate their current systems if they want to compete.
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