A Guide to Data-Driven Marketing and Big Data Marketing
10 min read

A Guide to Data-Driven Marketing and Big Data Marketing

In an increasingly digital world, it’s now more important than ever for marketing to be data-driven and to harness the power of big data analysis.

Despite this, many businesses still focus on traditional forms of marketing. For example, using studies or assumption, combined with trial and error campaigns to target their audience. Today, this kind of approach is no longer feasible. Indeed, customers are much more knowledgable and can gain access to competitors at the click of a button.

In this guide to data-driven marketing, we hope to highlight what this term actually means for your digital brand and showcase how you could benefit from working with big data. We’ll also offer our tips for moves you could make to help your team flourish in the world of data-based marketing.

What will we be covering in this guide to data-driven marketing?

  1. What is data-driven marketing?
      – Why is data-driven marketing needed?
      – Data-driven marketing examples
      – Data analysis in marketing
  2. How you can benefit from big data in marketing
      – Marketing data for personalisation
      – Efficiency and cost-saving
  3. Can in-house marketing benefit a data-driven approach?
      – Marketing data analytics: Tools and tech
      – Access to larger data sets

1. What is data-driven marketing?

Data-driven or data-led marketing focuses on using data from customer interactions and third parties. The data is used to gain insight into and predict customer motivations, preferences, and behaviours. Data marketing allows companies to identify trends, evaluate the effectiveness of their marketing, and enhance the customer experience. In turn, using these insights to target customers more effectively can translate into a greater return on investment (ROI).

The data used in this type of marketing is known as ‘big data’. It is gathered from various sources such as online interactions, browsing behaviour, or social media activity. Other information can also be collected, including online purchasing patterns. You can collect data from an array of devices including industrial equipment, smartphones, wearables, and other Internet of Things (IoT) items.

This big data provides evidence for digital marketing teams to create superior strategies and campaigns. But the data is not valuable unless it is accessed, extracted, and managed in the correct way to increase ROI. It needs to be activated to personalise customer journeys, generate conversions, and reduce churn.

There are different stages in the data marketing process:

  • Gather data (from social media, CRM, Google Analytics, heat maps, previous sales, etc).
  • Integrate the data and gain insights (analyse product demand, customer behaviour, affinity, and conversion paths).
  • Use your new insights to make strategic decisions – for example, audience segmentation and displaying ads on customers’ preferred platforms.
  • Take action – segment audiences, optimise funnels, target messaging, spend on ads/PPC/content marketing, and create an offer they can’t refuse.

Once you’ve acted, you’re still not finished. Data-driven marketing requires you to constantly track, accumulate, and evaluate your data to create an effective marketing strategy. The more data you have, the more successful your campaigns will be.

Why is data-driven marketing needed?

Data-driven marketing may sound like a daunting prospect for smaller organisations. Indeed, where do you get the data from? How do you store it? And how can you analyse it effectively?

While these are all worries several businesses may face, discovering the answers could be crucial to compete with competitors in the digital landscape. Operating with a data-led approach isn’t as daunting as it may seem and data analysis should now be standard practice in the world of marketing.

Customers are more empowered than ever before – wise to marketing messaging with droves of information at their fingertips. To avoid consumer scepticism, therefore, your business not only needs to utilise marketing data analytics to outshine the competition but also personalise content for your audience.

Data-driven marketing examples

There are several examples of how data-driven marketing can be used in practice for a brand. A simple but important example is how a brand utilises its display and social media channels for campaigns – without using data, you cannot be efficient with targeting your audience. For instance, if your customers don’t interact with posts on your Facebook channel, there’s little point in allocating advertising budget to that particular platform.

Using real-time data can also help your marketing team optimise a campaign in line with engagement. Moreover utilising big data in this way can be transformative to ROI.

When we think of using data to heighten customer experience, there’s no better example than Netflix. The streaming platform harnesses data incredibly effectively, creating a section to store recently watched shows for ease. However, the best example of using data for the customer, Netflix recommends content for consumers to enjoy based on previous viewing preferences.

Retargeting is another great example of using data for your marketing efforts. Tapping into previous purchases and patterns of buying behaviour can give a business invaluable information about a customer. Based on this gathered data, marketers can offer relevant deals and products – but crucially, at the right time. It’s also worth noting that in a cookie-less world new best practices may come into play with big players such as Google at the forefront.

Great marketers harness the power of data in their campaigns and efforts. Now you’ve seen some examples of data-driven marketing, you’ll understand how this information can be used.

Data analysis in marketing

As with any successful marketing effort, the process of data analysis in this field requires a process or strategy. Simply having the data isn’t enough, a marketing team needs to have a goal and purpose for the data and there has to be a plan.

So, what are the key steps for analysing big data in digital marketing?

  • Having a strategy in place first is crucial.
  • Identify goals – increasing revenue or heightening customer experience, for instance.
  • Do you have the right team in place to carry out the data analysis? If the answer is no, you may have to fill skill gaps.
  • Identify the type of data you require – results from a survey or social interactions?
  • Select the appropriate tools you need to automate, then collect and analyse the data.

It may be important to note findings from Bannerflow’s 2022 ‘State of In-housing’ report here. The study revealed that the businesses who were struggling the most with creative marketing identified lack of technology as their main issue. Therefore, implementing a strategy and framework for a digital transformation plan could be key to data analysis and resulting successes in marketing.

How is data-driven marketing different from traditional marketing?

All marketing focuses on understanding the customer, identifying their needs, and delivering a strategy to help meet those needs. However, data-driven marketing differs from traditional in the way it gathers data and allows marketers to appeal to customers on a more personal – and precise – level.

Traditional marketing relies on market studies (which can quickly become outdated) and assumptions about the audience. Data-driven marketing uses up-to-date information to fully understand and target audiences. It’s the difference between using trial and error methods to meet customers’ needs or using real-time data to connect to customers.

Traditional marketing is usually based on general assessments of the market for a product or service. It involves conducting focus groups and consumer surveys. While data analysts now use quantitative data mining and complex algorithms to uncover customer spending habits, traditional marketing is more at risk of human error.

As technology advances, it can accumulate increasingly complex data from customers. Big data is better at displaying and understanding market niches as it doesn’t rely on good response rates and sample sizes like market research does.

Data-driven marketing can track the entire customer journey in real time without the consumer even noticing. It can capture trends and predict future behaviours to create a more personalised experience. While data-driven marketing is important for offering deeper insights into consumer trends and behaviour, you can combine it with traditional marketing to detect the emotions, opinions, and attitudes behind that behaviour.

2. How you can benefit from big data in marketing

While we’ve already touched on the benefits of using big data in your marketing efforts, it bears highlighting further. A marketing team set up to gather information and marketing data analytics has the power to unlock the many benefits of data-led marketing.

What is data-driven marketing if not customisable? A brand can use data to personalise marketing for its audience, heightening the customer experience, and improving products. Marketers can optimise efforts to produce funnel efficiencies and save costs on media buying. The possibilities of big data marketing are countless.

Marketing data for personalisation

Personalised marketing and advertising are key for a modern audience. If a brand’s messaging or campaign doesn’t target the right audience at the right time, it will fall flat – especially in a competitive landscape. Consumers have a wealth of choice and if messaging isn’t relevant to them, they’ll simply go elsewhere.

Data-driven marketing helps create a depth of understanding of an audience to increase performance. This information helps to inform highly relevant, customised campaigns targeted to that audience and will avoid generic campaigns.

The same goes for customer experience. Utilising big data and analysis of it in marketing can markedly improve the experience a customer has with a brand.

For example, analysing browsing behaviour on your website can offer crucial information. Are customers frequently dropping off when they reach the same point on your site? This data can easily show you how you can improve the UX of your website and optimise conversion rates.

Customer satisfaction surveys can also provide fantastic information! While data-based marketing campaigns can tell you a lot about your audience and how to better serve them, big data can go further.

You can target specific audiences based on behaviour, demographics, and customer journey analytics. With a vast supply of data sources, you can discover smaller segments within broader customer groups according to demographics and interests. For example, a married millennial woman interested in cooking can be further narrowed down. You can target her specific age, preferred cooking types, and favourite chefs, restaurants, websites, and cooking shows. Once you’ve uncovered this new audience segment, you can create targeted messaging and personalised recommendations to secure more conversions.

So why is data-driven marketing important for audience targeting compared to traditional marketing methods? The majority (80%) of data is unstructured, meaning it comes in a variety of sources and different formats. It comprises raw information in its original form, such as everyday content like emails and social media posts. It also includes any non-document formats, such as images, audio, video, and sensor data from IoT devices.

Users expect a seamless experience across all digital touchpoints when dealing with a brand. In practice, this unstructured data can look like a user browsing a company’s products on a tablet, reading reviews via social media on a phone, making a purchase using a laptop, and contacting customer service via chatbot. But for the company, all data is generated from the same person in different formats.

Efficiency and cost saving

With efficiency and cost saving, using gathered data can be truly invaluable. When your marketing experts are making informed decisions and deploying campaigns based on data you can expect true efficiencies.

A marketing team can experience funnel efficiency, as you’ll optimise campaigns and efforts due to what’s attracting attention. Which elements of your content are moving buyers down the sales funnel? Optimise according to this information and it will translate into greater conversion rates and, ultimately, fantastic ROI.

Data-driven marketing lets you know when retargeting is appropriate for customers who have already shown interest in your product. Perhaps they’ve abandoned their cart or keep returning to a product page without converting. This personalised focus at the decision stage of the buyer’s journey prevents you from wasting time and resources chasing the prospects at an earlier point in the funnel.

It’s not just what’s coming in either; how about what’s going out? Digital marketing teams can use big data for their media buying strategies. Data creates evidence for where an audience wants to receive messaging and content. Therefore, efficiencies can be created in all aspects of this process. Save money by avoiding spaces that will not be fruitful – a successful marketing team will instead achieve an attractive ROI in this area.

Big data can save resources and reduce human inaccuracies while freeing up time for staff to focus on more valuable tasks.

The main ways big data can benefit your marketing efforts is by:

  • Getting more customers
  • Improving customer experience
  • Encouraging customer loyalty and reducing churn
  • Saving you time and money
  • Improving existing products/services or identifying new ones
  • Discovering gaps in the market
  • Identifying potential risks

3. Can in-house marketing benefit a data-driven approach?

In-house marketing can create several benefits for creative teams and this certainly includes how data is gathered, analysed and utilised. Bannerflow’s annual ‘State of In-housing’ report charts the rise of in-housing, where it’s finding its success and also how it’s evolving.

The 2021 report revealed that 73% of the businesses surveyed have moved part of their digital marketing in-house. Proving beyond doubt that in-housing is becoming increasingly popular. But how can in-house marketing truly benefit a data-driven approach?

Marketing data analytics: Tools and tech

We’ve stated that technology can be imperative when it comes to the analysis of data in marketing. The report backs this up by showing that over half of the surveyed marketing teams said they benefited from tech in some way, which translated into better use of data.

Interestingly, over half of marketers (58%) identified that using technology means that they are now using data better than ever before. The pandemic created headaches for unpredictable changes, meaning that having access to up to date and clear data instantly has become incredibly important.

Surveyed teams said they’d not only noticed that data was being used in a better way, but there were also production efficiency improvements.

When it comes to analytics, transparency and having real, accurate numbers can be crucial. Budgets can be tight and some players haven’t been completely honest in the past, so tech and tools can be transformative for accuracy.

Having the right tools to automate marketing data analytics is key. With a powerful tool such as Bannerflow’s Creative Management Platform (CMP), for instance, an in-house team can personalise advertising. This CMP can help an in-house marketing team with premium data-driven messaging and tailor content to individual viewers. Not only this but it can be achieved at scale – imagine how long that would take without an automation tool.

Access to larger data sets

Having people with the skills within a marketing team to analyse and use the data collected effectively is imperative. That’s where in-house marketing can shine, as there’s now no ‘one size fits all’ approach to an in-house set up.

What constitutes an in-house marketing team is adaptable. The main examples include fully in-house models, to a more traditional set up where an in-house team works with external agencies and a new hybrid approach. The hybrid model leans on a team of in-house experts and fills skill gaps with specialised external agencies.

Being in-house means a marketing team can have full access to the marketing data a team is collecting and shaping for deployment in campaigns.

The added beauty of in-housing is that it doesn’t only create access to the data. The control is within the hands of the brand’s marketing team rather than with external agencies. This means an in-house marketing team can have access to bigger and better data sets. And then use these data sets to help set strategies that produce campaign excellence.

In-house marketing can streamline processes and avoid hold-ups, so a brand’s efforts can cut through the noise, focus on the customer and deliver excellent ROI.

Conclusion

In the digital age, data-driven marketing is essential for outsmarting the competition, attracting and retaining audiences. The benefits of using big data in your marketing efforts, as a key element on strategies and for campaigns are proven to increase creativity, personalisation, efficiencies and save costs.

With the right team and tools, digital transformation implemented effectively and the creation of robust strategies, data-based marketing can be transformative to the success of your business.

Hopefully, this guide to effectively using data for marketing and advertising has helped showcase how your brand could shine within your industry.

Do you want to see how tools within the data-led marketing space could widen your reach and success? Book a demo of our premium CMP to trial this powerful platform for yourself and experience how the expertise of your marketing team with the right tools can help you flourish.

Bannerflow can assist your team with creating memorable, personalised creative campaigns, at scale.

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