How Data-Driven Marketing Can Reach New Customers and Boost Conversions

Digital marketing is an industry that has exploded in popularity and importance over recent years. Between 2015 and 2020, the industry saw an average growth rate of 69%, totaling a market cap of $260 billion in this latter year.

Alongside digital marketing, the data industry has also seen similar growth, with a total market cap of $161.6 billion in 2021. For marketing managers, the convergence of these two fields has been a productive integration into their marketing strategies. As data-driven marketing takes a forefront role in campaigns, the importance of data for companies is continually increasing.

In this article, we’ll be taking a look at data-driven marketing, demonstrating how data analytics can pull in new customers while ensuring your current user base is even more satisfied with the product.

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Let’s get right into it.

Why does data-driven marketing drive customer support?

A strong marketing campaign that is completely data-driven will pull from your company’s data sets and then craft insights that you can then act upon. These so-called ‘Actionable Insights’, allow your business to make smarter marketing decisions. Yet, as data becomes more of a viable medium, businesses need to turn to more comprehensive systems to store all of it.

Without a strong support system, many companies suffer from data silos. One way of getting around these is turning to data lakes and data warehouses. If you’re not sure which option would be best for you, take a look at a comprehensive Druid vs. Clickhouse comparison and go for the one that best suits your business.

With this in mind, there are several ways that data-driven marketing boosts customer engagement and brand support:

  • Allows for user segmentation and customization
  • Helps to optimize landing pages and product descriptions
  • Boosts customer lifetime value

Let’s break these down further. We’ll be pairing them with a case study to demonstrate the power of data-driven marketing.

Segmentation and Personalization

Every single company has a fairly enormous potential customer base. That is, one customer may look completely different from another, act in opposing ways, and have different tastes and interests. Due to this, a blanket marketing approach will often end up with many of your audience members either being alienated from your campaigns or feeling like your brand may not align with them personally.

Data-driven marketing is the simple fix to this problem, with advanced tools allowing you to see what your customers like best. By gathering data about your audience, such as what their likes and dislikes are, you’re able to build up a more accurate picture of what the perfect advertisement campaign would be for your brand.

Instead of putting out lots of different campaigns and hoping that one sticks, by collecting marketing data and collating it, you’ll quickly be able to develop a more comprehensive idea of what works for your business. The power of data-driven marketing ensures that you can accurately personalize your ad campaigns for your audience.

Data-driven personalization in action

A very successful data-driven marketing campaign was famously done by the skincare brand Olay. Typically, when you think of skincare, a specific image of the type of product consumer comes to mind. However, after collecting customer data, collating it, and analyzing it, the marketing team at Olay realized that their audience had another cross-over love.

The majority of their audience, alongside skincare, also had a love of horror movies. This strange combination wouldn’t have been realized without data analysis, with these two characteristics being practically opposites.

Due to this marketing realization, they developed a Superbowl ad in 2019 that revolved around #KillerSkin. This advert went viral, using horror movie tropes to highlight the effectiveness of the skincare brand. Alongside going viral and being a smash hit at the Superbowl, the clever and unexpected combination generated millions of dollars in business for Olay.

Data analysis was the core driving factor for this campaign, demonstrating how effective data-driven marketing can be at generating leads for new customers and reaffirming old ones.

Optimize Your Site

One of the most impactful results of incorporating data analysis and analytics into your marketing strategy is a more direct insight into how your customers respond to certain aspects of your company. Within your website, anything from the color scheme you use to the copy you employ can have an impact on your sales.

Using data analysis, you’ll be able to run more effective A/B testing on your page, optimizing every single aspect of your website. Let’s say that you launch two landing pages, one that 50% of your audience will see and one which the other 50% will see. Due to data collection about click-through rates, bounce rates, and time-on-page counters, you’ll be able to get all the information you need to decide which of these two pages is more effective at converting.

By changing small elements of your site and repeating these A/B testings with data, you’ll be able to continually refine your website and ensure it is effective as possible. You can do this on everything from the landing page to your contact page – everything is optimizable with data!

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Let’s see this in action

Google famously employed this strategy, testing 50 shades of blue on click-through buttons. On a different range of customers, Google presented a distinct shade of blue for their click-through buttons, with each 1% of customers seeing a different type of blue. Over the course of this experiment, Google used data collection and analysis to note down which blues were more clicked on.

Although this may seem redundant, by finding the blue that had the highest click-through rate, this one small change netted the company an additional $200 million in revenue. This one small change led to a huge impact, with data-driven analysis leading the company towards boosted revenue and more sales.

Boost Customer Lifetime Value

Customer lifetime value (LTV) is a metric that demonstrates how much a customer is worth across their complete history with your business. A customer that uses your site once to buy something worth $100 will have a LTV of $100, while a customer that makes 20 payments of $10 across two years will have a LTV of $200. In short, this figure represents how much money a particular customer has generated for your business.

An effective use of data-driven marketing is a surefire way to help increase your customer LTV over time. The main reason behind this is that by ensuring that customers come back time and time again, their LTV will naturally increase. Retaining customers is, therefore, a priority. Especially considering that it’s 5x more difficult to secure a new customer against having a regular buy again, tailoring your content to these repeat customers should be a central strategy.

One way that companies ensure customers like to come back to their store again and again is through loyalty card schemes. By collecting data, like when a customer signed up to your site, when their birthday is, and what their interests are, you’ll be able to launch a personalized communication with them.

For example, to celebrate their one-year anniversary of signing up to your site, you could send them a discount code – helping to get them back onto your site and build up a sense of loyalty. Equally, you could use the same tactic by recording data of when their birthday is, framing it as a gift.

Increasing LTV Through Data-Driven Insights In Action

Harvard Business School released research that demonstrated that an increase in customer retention of only 5% increased the total profits of that company by between 25-95%. This staggering statistic brings to light exactly how important customer retention is, with personalized data-driven marketing being a surefire way to bring your customers back with more frequency.

The UK beauty brand Revolution Beauty created a loyalty scheme called RevRewards. Within a matter of months, those that were on this scheme were by far the brand’s most profitable customers. Revolution beauty saw an increase of 378% LTV, with an additional 44% on their average order value.

Simply by recording information about the likes and dislikes of their customers, collating that information, then giving updates to their customers by emails about current loyalty scheme promotions, they enticed users back to their store time and time again.

By focusing on data-driven insights and making this a core part of their marketing strategy, they were able to get customers to come back to them in droves.

Final Thoughts

Data-driven marketing is one of the most powerful tools in a marketing manager’s tool belt. Instead of relying on guesswork, data insights can ensure that a business can make smart decisions. From customer integration to how they run and expand certain departments, data insights will always help businesses get on the right pathway towards success.

Google, Olay, and Revolution Beauty are examples of data done right, with large data stored being converted into insights on customers that actively help increase the business revenue. From obtaining new customers through A/B testing to enticing established ones through loyalty schemes, data is at the heart of effective marketing schemes.

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