Big data, as a whole, is defined as the volume, velocity, variety, and complexity of the data that is available to businesses on a day-to-day basis owing to the contemporary landscape of marketing. With the surge of digital commerce and social activity, agencies and teams have access to data that, when consolidated and managed efficiently, allow them to achieve higher returns on their marketing activities.
To put this into perspective, the online auctioning giant eBay estimated that the amount of business data collected doubles every 1.2 years, and IBM estimates that over 2.5 quintillion bytes of data are generated every day.
While marketers have always had access to large amounts of data, the scope of it all is even harder to quantify: from online purchase data, mobile device usage, social media interactions and behavior, browsing behaviors and lots more. However, big data doesn’t only refer to the amount of data; it also refers to the challenges and capabilities of businesses to store, manage and analyze the data to augment and drive business decisions that are cost-effective and timely, and enable effective product development and optimized offerings.
What Does Big Data Mean For Inbound Marketing?
This, now, brings us to big data in inbound marketing. Inbound marketing is a data-driven methodology that is centered on organically attracting customers through relevant content and interactions at the right time and right place. Keyword: data-driven.
However, just the mere availability of big data doesn’t lead to better marketing decisions. The sheer amount of data that’s available is enough to make marketers feel overwhelmed: what do we do with this data? Which data is relevant? How do we make sense of this ginormous mountain of information in a way that helps us make intelligent business decisions?
Before we get into the challenges of how marketers can organize big data, let’s take a step back, and first understand what kind of data is necessary to inbound marketers.
Mining for iNBOUND iNTELLIGENCE
1. Customer Data:
This data type generally encompasses personal, behavioral, attitudinal and transactional metrics that can be captured through marketing tactics like digital marketing campaigns, point-of-service transactions, online surveys, social media platforms and social interactions, online communities and customer loyalty or referral programs.
2. Operational Data:
Those are the metrics that track and define the quality of the marketing processes implemented by the business, such as those relating to marketing operations, resource allocation, asset management, and budget allocation.
3. Financial Data:
This data generally define the financial health of an organization including sales, revenue, profits and other data types.
Why Big Data Can Help Inbound Marketers?
Target and Acquire New Leads
If you’ve already defined your buyer personas, big data can help you acquire customers that fit your personas accurately. Big data lets you know what your customers are searching for, what challenges they’re facing and what drives them to seek your service out. When combined with your buyer personas, this data can help you identify and execute the right marketing strategies and craft messages that appeal to the right audience at the right time.
Retain Existing Customers
Big data can also help you extend the CLV (Customer Lifetime Value) of your existing customer by providing insights about their on-site activities, and helping you create value-based offers and content including customer support, upselling and cross-selling offers, and product upgrades. The data that informs these decisions can be derived from their product histories, social media interactions and information posted in customer feedback forms, for instance.
This information can also help guide your future marketing activities, such as focused product promotions based on which products generated the most favor among customers.
Identify Valuable Business Opportunities
Data obtained from both your own business and that of your competitors can help you identify new opportunities for product ideas and sales conversions that you might not have otherwise thought about. By analyzing what your own customers and those of your competitors are saying, you can gain an understanding of new challenges they are seeking answers to, and use it to create new business ideas.
Clearly Define Your Ideal Customer Profile (ICP)/Buyer Personas
The vast range of data available to you can help you form a clear picture of the key demographics that define your audience such as their age, work profile and geographical locations. In other words, big data helps you use intelligence on a granular level to develop your ideal customer profile from intuitions gained from very specific activities like the websites your customers visited, the pages they interacted with the most, and the social media profiles they followed or interacted with.
Also Read 5 Steps to Creating Smart Buyer Personas
Craft Effective Marketing Content
Facts and statistics pertaining to the search behavior and search trends can be a valuable tool to understand what topics currently hold the interest of users, how they’re searching for information around that topic and where that search volume is concentrated. This information can help in creating content - like blog posts - and inbound marketing strategies that are relevant, up-to-date and resonate with their buyers.
Develop Lead Nurturing Content to Edge Leads down the Funnel
Inbound marketing strategies are crafted with the aim of delivering the right content at the right time. Gathered intelligence, when processed with a CRM, can give marketers real-time insights on how prospects and leads are engaging with their content or product, and how that content is faring in terms of generating the expected Marketing ROI.
In turn, this will also give marketers a clear idea about which content was successful in pushing the customer down the funnel right up to a sale. Based on these insights, the marketers can develop effective workflows that result in quick sales, and create lead nurturing content and topics that resonate with their qualified leads and convince them towards a sale.
Integrate a Predictive Model into Your Lead Scoring Tactics
By combining data from their CRM and data mined from third-party sources, marketers can develop predictive models of lead behavior. Based on a successful lead’s past behavior and engagement with their marketing information, they can predict how future leads will behave, identify which actions defined that lead’s path towards a sale, and thereby, assign higher lead scores to those actions.
Challenges Marketers Face With Big Data
Earlier, we mentioned how the whole scope of big data is hard to quantify in terms of the volume and rate at which it’s available every day. While inbound marketers may not necessarily have to deal with such extraordinarily high volumes of data, the data they need isn’t insubstantial either: there’s still a large volume of formatted and unformatted data that needs to be handled, analyzed and interpreted. There are primarily three main challenges that need to be addressed:
- What Data to Gather. There’s so much data. Data of all types: structured and unstructured; customer-related, finance-related and performance-related; data from internal and external sources… well, you get the picture. Data needs to be organized and grouped in an intelligent way. Not only that, though: it also has to be the right data.
- How to Gather It All In One Place. As the volume of data continues to grow and change each day, it becomes harder to analyze and track the data and reach actionable decisions in time. There needs to be a means to aggregate all necessary data to analyze it and interpret it in real time.
- How to Turn Data Into Business Growth. Once you have all your data in one place, you cannot rely on intuition alone to garner the right insights. Furthermore, insights drawn from your inbound campaigns will require you to identify patterns and trends in the data and predict outcomes to drive growth-driven decisions.
How Businesses Can Handle Big Data?
At this point, it’s basically a given. Marketing automation that uses an all-in-one dashboard like HubSpot can help you consolidate all the data into clearly-defined metrics, from which you can infer and intuit the performance of your inbound campaign across each and every channel that you’re using: your website, your blog, your social media platforms and other marketing channels.
Marketing automation also provides clear insights into crucial aspects of your campaign such as your lead behavior over the course of their journey down the funnel, and thereby helps create meaningful nurturing campaigns for future customers. Lead scoring can also be automated; and warm or sales-ready leads can be automatically assigned to your sales team.
Math marketing combines data and artificial intelligence marketing to predict and maximize a business’s marketing campaign success and MROI. This method uses precise formulas, algorithms and predictive analysis to exploit data to increase lead generation and increase customer retention.
The predictive model associated with Math Marketing also allows marketers to identify, fix and pre-empt any issues that could affect the campaign: it essentially lets the data determine what happened during the campaign, why it happened, what is happening after the issue was identified and fixed, and what might happen down the line.
Big data will only get bigger. As a result, marketers need to understand and leverage the potential of the information, and find efficient and proactive ways to acquire, analyze and interpret the data in a timely and accurate way.