Globally, data is growing — from 45 zettabytes in 2019 to a projected 175 zettabytes by 2025, according to IDC, yet what matters most for businesses is not the volume of data but rather knowing how to use it effectively – creating actionable insights that assist in decision-making processes and delivery of strategic objectives.

According to McKinsey, businesses that have successfully integrated creativity and analytics have grown twice as fast as those that haven’t. Pairing creative talent with data scientists in an approach dubbed “marketing engineering,” is clearly paying off.  Creativity can be helped, guided, and validated by data and analytics. And the reverse is also true.

Seeing how data trends are disrupting whole markets, ambitious organizations are also adopting a data-driven culture to avoid falling behind their competitors and to see results. The opportunity to deploy data and analytics has accelerated the speed at which companies can enter new markets, with new solutions, and quickly challenge or displace traditional competitors and market leaders which is why, according to a recent Forrester report, data-driven companies “are growing at an average of more than 30% annually.”

Results from a McKinsey Global Institute study indicate that, data-driven businesses are 20-plus times more likely to acquire new customers and six times more likely to keep them. 

So how is this playing out in the world today?

Big data is helping to create better B2B loyalty programs

B2C loyalty programs are common methods of increasing customer engagement and now they are appearing in the B2B market, too. Loyalty program can be comparatively more complicated in B2B transactions as there are usually numerous decision makers, however the use of big data models can determine which entities are most likely to show future commitment and help B2B organizations tweak their program offerings. Offering referral program options, rebates and/or discounts based on the number of transactions are just a few ways these are being put into practice at Fortune and FTSE 250 companies to drive growth.

Big Data can help determine the content types and topics that B2B customers are looking for most.

Content marketing is an essential ingredient for interacting with potential customers and growing sales. According to the Content Marketing Institute  analytics tools ranked as the third-most used technology for content marketing efforts.

Big data allows organizations and technology-enabled consultancies like Hundred to investigate which types of content delivered the highest ROI for the organization – this helps to enable data-driven decisions regarding where to allocate marketing budget that push the B2B company forward towards achieving their strategic objectives.

Similarly, big data analytics shows how customer engagement with content differs as a person moves through their buyer journey. For example, a B2B customer likely won’t engage with a large content asset, such as a buying guide or white paper, until they are at a sufficiently late stage in their buying process. A person who is earlier in the buying process might have more appreciation for a sales sheet with a bulleted list of product advantages and benefits.

Big Data can help to improve customer service methods and impacts

A 2018 Accenture report found that 79% of B2B companies use chatbots for customer service, and 73% depend on virtual reality (VR) or augmented reality (AR) for customer service purposes. Those statistics indicate that B2B companies are increasingly on board with high-tech options for addressing customer needs.

Alternatively, if a B2B company has multiple customer service channels — such as telephone support, live chat and email — big data analytics can indicate which methods are used the most during certain days or times. Such insights could improve decision-making, such as helping a company determine whether to extend its phone support hours or hire another person to respond to email questions. B2B companies can increase the effectiveness of their customer service efforts even more by using big data platforms to analyze customer sentiment in conversations with a chatbot.In this scenario, data analysis could pick up on specific words that likely indicate extreme frustration. A company representative could be notified of the customer’s situation and take over the conversation to resolve the issue.

The examples on this list highlight why B2B professionals should take big data seriously. The insights they receive from analytics tools could positively alter how they operate and reshape the anatomy of their organizations. In order to leverage the knowledge and data, all departments of the company need to become more integrated and interconnected. 

Knowing where to focus marketing efforts is important. With big data, you can achieve more with precise targeting, lead generation, and increasing sales. Combined with predictive analytics and AI methods, big data can help us determine where the customers will be, how they may act, and what they may “do”. This responsiveness translates to better demand generation, the ability to create new markets and segments, while enhancing and optimizing both multi-channel and omni-channel marketing experiences.

Customer analytics, search engine optimization (SEO), email marketing, push/SMS/mobile app marketing and digital ad platforms are just some of the areas where big data brings a competitive advantage. As Justin De Graaf, director of data strategy and precision marketing at the Coca-Cola Company notes, data is particularly vital for Fast-Moving Consumer Goods (FMCG) brands to thrive. 

“Data plays an increasingly important role in marketing and product development. Consumers do a great job of sharing their opinions with us – either by phone, email or social networks – that allow us to hear their voice and adjust our approach. We often talk about why we have two ears and one mouth – it’s better to listen more than we speak. This holds true with our approach on consumer input. Data is also helping us create more relevant content for different audiences. We want to focus on creating advertising content that speaks differently to different audiences. Some people love music. Other people watch every sport no matter what time of year. Our brands are already visible in those spaces, and we’re working hard to use data to bring branded content that aligns with people’s passions.”– Source: https://www.adma.com.au/resources/how-coca-cola-uses-data-to-supercharge-its-superbrand-status

To compete in the digital economy, businesses have to become increasingly data-driven. The Covid19 pandemic has only underscored the critical importance of having reliable data to inform organizational decision-making. In organizations with strong data cultures, important decisions are informed by data and analytics and executives act on analytically derived insights rather than intuition or experience, yet many organizations struggle to operate in a data-driven manner.

Research of 400 senior marketing executives from around the world shows that more than 70% recognize the need for a major digital transformation of their marketing and sales departments to give their company a competitive edge.

A recent Deloitte survey of U.S. executives found that 63% do not believe their companies are analytics-driven and 67% say they are not comfortable accessing or using data from their tools and resources.

Data from surveys taken over time suggest that the problem may be getting worse, a NewVantage Partners survey of C-Suite executives representing over 70 Fortune 1000 companies taken in 2020 found that only 37.8% have created a data-driven organization with 54.9% of companies saying they do not compete on data and analytics.

Technology is not the issue; it is the process of cultural change

While digital-native companies like Amazon and Alibaba have strong digital cultures, many organizations are struggling to make progress. Invariably this is because few undertake initiatives directly aimed at achieving the desired culture change.

In a New Vantage Partners survey of large US firms more than three quarters reported that business adoption of big data and AI initiatives remains a major challenge. 95% of them said that cultural, organizational, and process challenges presented the biggest roadblocks to adoption. Only 5% cited technology as the problem.

An organization’s adoption of big data requires addressing issues of organizational alignment, change management, business process design, coordination, and communication.

These are issues that involve people and communication and understanding. Organizations must start by identifying and asking the critical business questions that will drive business value and identify and address the critical human and organizational issues that will ensure successful adoption; the technology then follows.

There is no denying that data analytics can provide connected and actionable insights about people’s habits, behaviors, mindsets, choices and decision-making abilities. Brands will continue to need this level of insight to reach customers in an increasingly cluttered landscape where people are asking brands to become more culturally relevant and expect an omnichannel personalized experience.

To align marketing priorities with the business objectives, create highly relevant customer experiences, and maximize the marketing return on investment (MROI), organizations must enhance their analytics capabilities and ensure marketing, IT, legal, and finance teams can collaborate efficiently and effectively to enable quick campaign approvals and execution.

For big data-driven management to be truly embraced, cultural change and business transformation must be adopted at all levels of an organization. Many organizations, impatience to see results can lead to reckless investment in (and abandonment of) technology initiatives or the launch of and lack of follow-through in culture change programs across the organization. 

In the face of increasing complexity in the markets and customers they serve, chief marketing officers often struggle to keep pace with competing business demands, proliferating channels and partners, and a disconnect between the talent they have and the capabilities they need.

This doesn’t mean senior marketers can’t improve performance despite this challenging environment. What marketing organizations need are analysts. People who can employ technical capabilities to represent and interpret big data sets, to tell a compelling story. For example, how a particular segment of customers is behaving or is likely to behave, towards a particular product launch, or which mix of messages and offerings would be most appropriate to different customer segments.

In today’s C-suite, data makes the rules, which is why executives have increasingly turned to technology-enabled consultancies like Hundred for strategic integrated sales and marketing advice over the past several years.