Back in the old days, marketing was ridden with a lot of guesswork. Sometimes, unexpected campaigns brought new leads and converted prospects into customers. Other times, the best-designed campaigns flopped, the market remained unmoved and all you could hear after the launch of a campaign was silence.
Data-driven marketing rose from the pains of this insecurity and took on the overwhelming growth of data for its support. It refers to strategies, processes and campaigns in marketing, all of which are guided by the data collected from customers via digital analytics, market research, qualitative insights, and customer behavior.
Data-driven marketing offers multiple benefits:
1. Better business results. From cutting costs to producing higher returns on ad spend, using data to drive your marketing often leads to a healthier bottom line.
2. Improved operational clarity. Data improves operational clarity in three ways:
a) It’s clear whether or not a campaign was successful. In data-driven marketing, you evaluate campaign performance by measuring the success with data: has the number of new potential customers, or prospects converted to customers, reached the desired goal?
b) It takes the guesswork out of the game. Whenever you set up a marketing campaign, there are multiple ways to hit your goals. In data-driven marketing, you don’t have to argue about which creative is better - just choose your top contenders and let the market decide. From A/B experiments to machine-learning algorithms embedded in ad-buy software, data-driven marketing takes multiple creatives and uses data to decide which one works best for our customers.
c) Strategic alignment. Before turning to data to determine our future marketing efforts, leaders had to guesstimate which channels were the best performers. Some felt that TV commercials brought in the customers, while others argued it was the multiple conferences that they attended. With data-driven marketing, you can measure the effectiveness of each of your channels by attributing leads and purchases to them directly. This clarifies which channels you should double down on in your future marketing strategy.
3. Refined customer experience. Data-driven marketing offers information that helps you to tailor your campaigns to every customer. By personalizing the creatives, marketing messaging and value propositions based on data, customers find that your marketing speaks to them on a personal level and so are more responsive to your products and services. Personalized marketing is not just more effective, but also more satisfying. The improved customer experience leads to higher trust and loyalty, which in turn results in customers loving your brand and repurchasing in the future.
Data-driven marketing boasts a wealth of benefits. However, it’s value also runs on a far deeper level: it changes how companies are structured and how they run their operations.
Instead of egos and HiPPOs (highest paid person's opinion) running your strategy, you decide to give your customers a voice when it comes to shaping and developing your brand, communications, and product.
This opens the door to more customer-driven business development, as well as empowering employees to voice their ideas. Any idea can be tested and win over the customer's heart when data - not HiPPOs - is the ultimate judge.
Data-driven marketing can take on many different forms. We’ll now take a look at a couple of areas and showcase what data-driven best practices can be implemented to boost your marketing growth.
GreenPal - the ‘Uber for Lawn Care’ - is a lawn mowing service. Their Google ads were performing well, but they wanted to improve them with personalization. By analyzing the local prospect user base, they identified a gap between the communication of their digital ads and the needs of the customer base. Namely, customers from different regions of Nashville were more attracted to the low price of the service than the usual value proposition, i.e. the ease of having someone else mow your lawn.
GreenPal segmented the ZIP codes of the price-sensitive customers and localized the targeting of their ads with a personalized ad headline: ‘The Cheapest Lawn Mowing in Nashville. Lawn mowing from $20’. This boomed their ad success with a “200 percent lift in click-through rate and a 30 percent lift in on-page conversion”.
Obama’s presidential campaign may have been almost two mandates ago, but the methods used will go down in history for their incredible success. The majority of the campaign funds were raised via email, and in order to make their outreach successful, they conducted experiments with the email to optimize it.
Concretely, multiple subject lines were shortlisted as the best contenders and emails were sent out to smaller batches of the email list for an A/B test. The winning email of those experiments was then sent to the remainder of the newsletter list.
How impactful were those tests? According to Toby Fallsgraff, Email Director, and Amelia Showalter, Director of Digital Analytics, the difference between the best and the worst email equated to $2 million dollars. This is why testing pays off.
Dove, one of the leading beauty product providers, heavily researched their target audience outside of the domain of cosmetic usage, with the aim of better understanding who they are as people, not just consumers.
In the research, they identified that 80% of women were exposed to negative body talk online.
To address this online undermining of women, Dove launched a campaign under the #SpeakBeautiful hashtag, which focused on positive body talk. The campaign did not sell Dove’s products directly or inform potential customers of their offerings.
Instead, Dove gained recognition as a positive brand. The results?
Data-driven marketing examples can be tempting. They sound exciting, they’re novel, and any marketer worth their money is itching to try them. But as with every other activity, being fast to market or having good ideas is not enough. To nail your marketing, you need to deliver consistently. Execution is everything. To execute successfully, implement a data-driven marketing strategy to drive your efforts to fruition.
Whether you work in a B2B niche or run a B2C e-commerce site, the general steps of implementing a data-driven marketing strategy are consistent across organizations of various sizes, verticals, and levels of data maturity:
1. Start by setting business objectives. Every marketing strategy, including a data-driven one, begins with setting business objectives. The business objectives should be formulated as S.M.A.R.T. goals to make them effective:
Specific: the goal needs to be specific enough for people to immediately understand what the bottom line is without any ambiguity. Are you trying to raise ROAS by 12%? Hit a specific revenue goal? Increase the average weekly number of new leads by X amount? Are these goals for all products, or just specific ones?
Measurable: Every goal needs to be measurable. Some goals are easy to measure, e.g. the number of new prospects, customers, and ROI changes. But consider some of the harder things to measure, such as social media engagement (we could count the number of likes, shares, comments, or all of the above) or brand affinity (hard to measure, unless you implement a sentiment analysis over your customer reviews or check NPS changes). In general, ‘softer’ goals (those which aim to improve customer satisfaction, opinions and values) are harder to measure, but not impossible.
Achievable: The goal needs to be attainable. If it’s impossible to achieve, you are playing lip service to the data-driven marketing strategy and will probably feel demoralized by the impossibility of it.
Relevant: The goal must be beneficial to the company. This does not necessarily mean increasing the revenue (by acquiring new customers or upselling existing ones); it could mean increasing brand loyalty or customer satisfaction. The latter still affects the bottom line, but on a longer time scale.
Timely: The goal needs to be set against a timeline, with a start and end date. This prevents you from constantly waiting for the results of a campaign. If there are no results, that’s fine - the goal could not be determined as successful and you can move on to other goals.
2. Translate business objectives to marketing campaigns. Every business goal can result in multiple marketing campaigns and strategies. This is where your expertise has the opportunity to shine. Formulate multiple tactics to reach your goal and shortlist the best contenders based on your experience.
3. Establish what data is needed for the launch of the marketing campaigns. Some marketing campaigns require data before they can be launched. For example, imagine you are launching an upselling email marketing campaign - you would need a list with customer information (name, age, previous products, recommender product for upselling for every individual). Other campaigns can only be evaluated using data after the launch, for example, Facebook remarketing ads to convert leads from a landing page blog to paying customers. Establish exactly what data you need to make the campaign great.
4. Implement a data collection process. Once you know the data that you’ll need for your marketing campaign, figure out how to collect it. In some cases, this can be trivial (e.g. Facebook campaigns can be run within the Ads management platform). In other cases, this can result in a cross-departmental chase for engineers. Use data management platforms that help you to aggregate data about your customers from different marketing platforms (e.g. Google Ads, Facebook Ads, Linkedin Ads, Bing Ads, CRM, Email marketing tools). Enrich the data, then analyze it (for instance, use a recommender algorithm to understand which products you should recommend to each customer).
5. Run the marketing campaign.
6. Evaluate the marketing campaign based on data. Evaluate the success of the marketing campaign by comparing it to the SMART goal. Have you reached the predetermined measurable success that you set out to achieve?
7. Automate. When you nail your goals, automate them - there’s no need to manually run the same data collections and marketing campaigns. Rely on software and tools (such as data management platforms), which re-run all of the aforementioned steps for you. This saves you time while guaranteeing a high standard of repeatable marketing processes.
There are two types of challenges that accompany the implementation of data-driven marketing: organizational and data challenges.
Organizational challenges refer to the expertise and skills that are found in-house. A lack of data engineering and analytic skills (or the lack of time faced by the workers who have those skills) can severely impede your data-driven progress. Trying to collect the relevant data for your marketing efforts by hand, without the experts, can slow you down. Thankfully, there are data management platforms that can do the heavy-lifting for you.
There are also data-specific challenges that arise when implementing data-driven marketing:
Many of these challenges can be solved by relying on a trusted data management platform.
The right data management platform can help you to quickly achieve better results with your marketing.
Keboola is an all-in-one data platform, built to accelerate data-driven company operations: