3 ways big data is transforming marketing and sales

3 ways big data is transforming marketing and sales

With the Internet going mainstream 20 years ago, big data is transforming marketing and sales like never before.

Today, marketers and sales leaders are in the midst of a major technology-driven transformation. We have access to a flood of data, giving us visibility into customer behavior and effectiveness of our marketing programs. However, we are a creating a new silo of data with every marketing application that goes live. And so what we lack is a visibility into the end-to-end customer journey or the aggregated customer view. We need to know better, and this is why it is crucial to understand how big data is transforming marketing and sales.

Ways how big data is transforming marketing and sales

Identifying valuable opportunities

In order to discover opportunities, you need to pull in relevant data sets; not just from within the company, but also outside it. Once you have the data, next comes analytics. And analytics leaders believe in ‘destination thinking’, and not mass analysis of all the data collected. Destination thinking involves writing, in simple sentences, the questions you need answers for or the business problems you wish to solve. Big data and its analysis is transforming marketing and sales by going beyond the broad and vague goals, into a level of specificity. For example, a company may have 20 percent of the overall market, a micro market analysis may reveal that while it has 60 percent of share in some markets, its share in others may be as little as 10 percent.

Starting with the consumer decision journey

Consumers today surf multiple channels and use an array of devices, technologies, and tools to fulfill a task. Data collected from these sources is critical to understanding the decision journey of a customer; this helps in not just identifying new customers, but also retaining the existing ones. Let’s take the example of B2B companies understand the importance of mapping customer decision journey in marketing and sales outcomes. 35 percent of B2B pre-purchase activities are digital in nature, and so B2B companies need to invest in websites that can effectively communicate the value of their products, SEO technologies to find potential customers and social media for spotting new sales opportunities. The underlying idea is for marketing and sales leaders to use big data for forming complete pictures of their customers; thereby, creating products and messages that are relevant to them. Big data helps you gain clarity, deliver more personalized products and services, up the ROI on marketing spend, and lift sales.

Adding speed and simplicity

The rate at which data is growing worldwide is proving to be quite daunting for most marketing and sales leaders. However, approaches like predictive statistics, natural language mining, and machine learning that allow for processing of vast amounts of data, employing a self-learning process, help create better and more relevant interactions with customers. For this, companies need to invest in what is called as algorithmic marketing. Algorithmic marketing uses big data and lends speed and simplicity to your marketing and sales activities. For example, you cannot just track keywords automatically, but also update them every 15 seconds based on ad costs, customer behavior, or change in search terms used. Advanced analytics, when applied to big data, not just speeds up your efforts at marketing and sales, but also shields your customer service operator or field sales representative, from analytical complexity; all you have in hand are simple guidelines and recommended actions. Big data is a goldmine for marketing and sales leaders, waiting to be mined for umpteen possibilities. You need to think beyond immediate revenues to make the most of it.

Christina McCormick

Marketing Leader | Impact Driver & Relationship Connector

7 年

Interesting read

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Numa F.

Manager BI Analytics | Data Engineer | Big Data Engineer | BI | Power BI | Tableau | IA | Machine Learning | Python | R | ML Engineer | Mlops

7 年

Excellent article.

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Basweshwar Swami

Sr.Software Engineer - Quality Assurance

7 年

interesting article

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David Nightingale

Enterprise Data Architect BI Consultant

7 年

hmmmm

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Richard Onions

Account Manager for Team Software

7 年

Excellent article which is straight to the point and raising a few good comments. I understand that there can be bad data, but if you do not have a strategy then the data you collect is meaningless. Thank you for the additional link to cygnet as it was also an interesting post.

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