With increasing modernization and advancement in technology, big data analytics has evolved as a revolutionary concept which has completely changed the way B2B marketing is handled. The potential that big data holds for e-businesses is being tapped to the advantage of both, the customer as well as the organizations selling their products or services. Valuable data available on the Internet is scraped by professional services, making data crawling the need of the day.
Insights derived from customer buying behavior hold hidden opportunities that can ultimately help boost sales. The Big Data revolution has brought a sea change in a way that analytics-driven marketing has become central to all organizational operations for every industry vertical.
Quite surprisingly, it is not just the retailers who are feeling the heat of the digital revolution, but most B2B marketers are also not satisfied with the results of the programs that are a part of their current online marketing mix. Even though the use of Big Data is known to have arrived on the circuit for quite some time as a part of the lead generation and nurturing process, most B2B marketers are still in the process of identifying ways to manage and leverage the influx of information collected from prospective clients. The question goes beyond just Big Data awareness; while some may understand why data is needed and want to readily implement a Big Data strategy, they face the problem of acquiring data.
Data acquisition is a challenging step to when moving towards a Big Data solution. Fortunately, this problem is today addressed by specialist providers who offer Data as a Service (Daas). These DaaS use machine-learning and cloud computing to crawl sites and return data (structured or unstructured) format. Data crawling is the first step towards adopting an analytics-driven approach to gather business intelligence and improve operational processes.
B2B marketing is taking a new shape. Though it may be difficult to measure the impact of marketing efforts, tying together the pieces of big data may present a very clear picture of which content types are driving action for your audience segments.
According to a research from Crain’s BtoB Magazine, 63% of marketers are unsure if their marketing mix is effective enough to help them meet their sales demand. Interestingly, a whopping 88 percent of the participants of the survey said that they are using email marketing as a part of their online brand promotion, even as 56% of them agree that brand promotion is a key area of focus.
Even though the B2B marketers who were a part of this survey consider email the most effective channel for lead generation, they do not realize is that this customer data can be leveraged to the extent that it can be used to optimize and personalize content in email newsletters. Another survey found that even though Big Data seems to have created enough buzz around all industry segments, only 25% of businesses are putting their own data into timely action.
Small B2B organizations tend to ignore their own customer data and invariably end up sending across the same email to everyone on their list irrespective of whether they are a customer or still in the sales pipeline. Lack of basic segmentation costs a lot in the shape of very low open and read rates. On the contrary, customer data can be utilized effectively to discover and segment audiences for better lead conversion, and in the long run, better email marketing metrics.
This concept seems to be backed by a research from Monetate that goes on to show that email marketing targeted at specific segments delivers a 30% higher open rate and 50% higher click-through rate.
Out of the many ways this can be done, one other way to generate email addresses and building a database is by employing a professional data crawling service provider. Usually, all it takes is listing the site and specifying the fields one wants from the website. The DaaS provider automates the data crawling and extraction process to return the list (or emails) from the desired list. Scraping is a valuable service that can be synchronized to market dynamics. Another advantage is that data so gathered is analytics ready.
With surging data volumes the gathering and analysis of data laid bare the fact that marketers lacked clear strategy to manage data. While the focus was on the collection of as much data as was possible, the process in which this data could be leveraged for the enhanced profitability of a business took a backseat.
Evolution in the Big Data analytics concept has given way to newer methods of utilizing the data. The beauty of analytics lies in the fact that the one data-set can be used to derive different inferences that may impact the overall profitability of the business. There are a number of ways in which this data can be used to impact the sales and revenue, but the more predictive marketing decisions seem to evolve from the collection of large volumes of behavioral data.
If marketers want to add value to their data, it is important for them to collect a lot of behavioral data and then reap the benefits of competitive advantage through predictive analytics. The success of an organization today not just depends on riding the big data wave but on being able to make better use of big data to improvise better marketing processes and deliver more relevant, integrated results.
In a nutshell, email marketing for B2B marketers needs to be able to convey the impact of the message. This customer-centric approach may require sending compelling messages in a customized format to be able to ring a bell for both, the customers and the prospects.
Businesses need to look at their processes and identify the areas where changes are needed. Customer insights and real-time analytics make it possible to be able to leverage the benefits of big data analytics but this task requires marketing systems for data collection, automated analysis, and targeted distribution.
As Big Data seems to have arrived to stay on, there is absolutely no chance that B2B marketers can survive without investing in analytics. While change is inevitable, the only thing that should be driven by that change is growth. Accepting change and driving the change hold meaning and purpose only as long as they aid in the overall growth in productivity in the long run.
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