Since the advent of big data, brands have begun to collect customer behavior data – albeit cautiously. Advertising companies, however, lack the resources that have the necessary skills to harness the information received from this amount of data, which is often in the scale of petabytes.
This is where big data services and solutions providers step in. They help advertising companies or marketing departments of brands to derive actionable intelligence from various channels that they are using to gather customer data.
In other words, they help advertising firms address the marketing issues by providing them with analytics on the online activity of the customers and point of sale transactions. This leads to real-time identification of dynamic trends, which can be leveraged to create marketing campaigns on the fly.
Role of Big Data in Advertising
Create targeted and personalized ad campaigns
Big data is gathered through as many channels as the brand sees viable to analyze customer behavior. This is then run through specialized analytics tools that display information in a visual format that shows customer behavioral patterns. Through this, the advertising companies can quantify the retention costs, average transaction values per customer, and average customer satisfaction ratio.
All these factors help boards formulate campaigns that are tailored to customers within a certain segment based on their geographical location, buying pattern, and other such interdependent criteria. For example, if a user likes a smartphone post on Facebook or searches Google for specifications of the smartphone, then (s) he will see targeted ads on her/his feed offering personalized discounts.
How to Use Big Data to Leverage Social Media Analytics
Even in the case of dynamic social media trends, big data can identify catchphrases that can be used to create marketing campaigns immediately. For example, during a power failure in a Super Bowl match, Oreo floated a social media campaign that told customers that they can still dunk in the dark!
These kinds of campaigns whether targeted towards a particular customer segment or personalized for a particular user, strike an emotional chord that serves the purpose of both – resulting purchase and customer retention. This is possible only because of big data ‘analytics’ and not just big data.
Identify customer motivations
Another important aspect of advertising is identifying what drives the brand’s customers’ buying patterns.
Do they buy around the holidays? Do they buy when they are bored? Do they buy things only once or twice a year or they’re regular buyers? Do they spend huge sums in one-off instances or relatively small sums on a regular basis? Is their buying pattern influenced by the latest trends and celebrity endorsements or they are independent in their choice of merchandise?
Big data analytics equips your marketing team with just the right information to determine all such factors that were a distant dream a decade ago.
Generate predictive analytics to counter the ad fraud problem
In measuring impressions and customer behavior, there is a major glitch of gathering false information, as most of the ads are liable to be viewed by bots these days. This means that a large portion of the budget allocated to creating the advertising videos may not actually be reaching its intended audience.
Big data helps formulate the tactics to counter this through predictive analytics. Brands can define the type of customers that should be shown the ads, making it more probable that a human click on it and views it as it is aligned with his/her interests.
Predictive analysis also does away with the traditional method of running a campaign by various departments before launching it, since it already provides the marketing teams with the possible customer behavior that will be triggered by the campaign. Only those campaigns that predict successful customer conversion/retention that will result in purchases will pass as viable campaigns, thus sparing the team members the work of manual analysis.
More Big Data Tools for Small Entities
Small companies have typically been unable to apply this highly technical strategy to analyze the audience in the past. But as AI and machine learning becomes an integral part of modern digital marketing, on a smaller scale, many companies are starting to offer big data.
For practically any part of their social media and marketing campaigns, there are many digital platforms and resources that small businesses can use. Business Intelligence solutions also provide customizable pricing plans based on the size of your business and the number of employees that need access to the data. Even some of the modern most popular CRM and marketing solutions are beginning to integrate AI capabilities, such as Einstein from Salesforce and AI-supported extensions from HubSpot.
AI and Big Data have the power to change the world the focus on social media marketing of a small business. Efficient pricing solutions allow businesses to make full use of this technology without having to select and choose only the features that fit into their budget. This contributes to making this type of technology even more available to businesses of all sizes by providing the resources on platforms that many larger companies are already using.
Big Data for Everyone
Maybe the greatest change people will understand is that big data is no longer the arena of big business with large amounts of resources. With companies like Nextiva offering tools for a small subscription fee per year, or a one-time fee, big data can even be used by small businesses.
This will make use of information not just an advantage, but a requirement. If you haven’t brought your company into the big data field yet, you’re missing out and it’s time to change that if you remain ahead of the competition.
The above points conclusively determine that using big data is significantly helpful to advertising companies. Big data solution providers can effectively boost their turnover by helping them turn their big data into actionable intelligence through the right analytics, tools, and dashboards.
What are your views on the role of data in business?