Over the past decade, it has become evident that Data is the oil of any business; its absence will cause dependence on trial and error for any operation. Big Data has been popular because it allows more extensive capabilities for gaining accurate insights, and companies can capitalize on it heavily. There are various ways to leverage Big Data in marketing and sales to gain a competitive advantage.
Big Data is the collection of enormous quantities of structured and unstructured data from multiple channels, which would be impossible for traditional models to analyze effectively. Data analysis techniques and analytics tools are used to examine and process the data. This Data offers possibilities to build highly responsive and accurate campaigns with its ability to precisely target the three critical Ws – who, when, and what.
How Big Data Affects Marketing
Since sales and marketing have different targets to cover and measure success, it has often led to disagreements. Applying the old and siloed approach to the various teams causes conflicts. Big Data analytics helps collate all these different systems into a unified structure with a collective set of particular goals. These systems act as data sources that help set up different segments and audiences for marketing, create a precise go-to-market strategy, and guide targeted advertising campaigns.
Big Data helps reshape the company’s anatomy, provided all the departments are interconnected and function in an integrated way to leverage the benefits.
Knowing where to focus marketing efforts is essential, and with Big Data, businesses can achieve amplified results in lead generation, targeting, and increased sales. When combined with AI and analytics, Big Data can identify target audiences’ locations, preferences, behavior, and activities.
This responsiveness delivers a better ability to create new market segments, demand generation, and opportunities to optimize and enhance omni-channel and multi-channel marketing experiences.
B2B sales and marketing now have only one end goal – providing complete and exceptional customer service across all channels. And this experience can be provided through customization and personalization.
Personalization helps in relevant and precise targeting, like creating an offer, webpage, ad, or coupon that shows different copies for existing or frequent visitors compared to new ones. This strategy can be tweaked according to the type of business and types of marketplaces- like digital storefronts or online shops.
Another example would be customizing the price based on the customer-product combination, which is valuable for B2B businesses. Each customer is different, and there must be an automated data stream to help optimize and allow orders and reorders with information from earlier purchases. Analyzing a complete data set to decide the most beneficial customizations can help boost conversion rates.
Big Data and ABM Strategy Go Hand in Hand
The challenge B2B faces compared to B2C is the number of users available for conversion. But, even though these numbers aren’t large, the customers demand highly customizable services. Here, every customer acts as an island himself, and segmenting them into groups does not stay relevant anymore. This issue has led to the birth of the ABM approach.
With ABM, treating every account as a separate market becomes more manageable, causing a clear shift from the regular MQL strategy. Therefore, Account-based Marketing is one of the most popular approaches that leverage Data and propel growth. The fundamental prerequisite for creating an ABM approach has precise, accurate, quality data that helps identify paramount accounts and makes targeting easier. With the help of demographic and firmographic data, identifying markets, reaching them across multiple channels, and delivering relevant content becomes a swift process.
Every organization has its set of distinct opportunities and challenges, but with proper technology like Big Data, organizations can reap the benefits, regardless of size. The key is high-quality data that drives better decisions. Data quality is the critical determining factor for building a go-to-market strategy, as every year proves, and this will continue to impact every single thing in the future.