Learn how to harness the power of data-driven marketing
Your marketing team wants fresh, effective strategies to generate new business and keep current customers coming back for more. Data-driven marketing can help you better connect with target audiences and build successful marketing strategies.
But when it comes to implementing new systems and approaches, discovering how to use data-driven marketing to develop those effective strategies can be a challenge. You’ll need to know where to start, what data is important, and which tools are best suited for your task.
In this article about data-driven marketing, you will learn:
- What it is
- The benefits
- The challenges
- How to create a strategy
- Data-driven marketing tools
- How to get started today
What is data-driven marketing?
Data-driven marketing uses customer data to create customized buying and creative messaging strategies. Personalized marketing means getting the message just right for choosy customers in a saturated market, and it’s one of the most transformational changes digital marketing has seen.
New technologies that automatically collect, combine, and analyze customer data are at the heart of data-driven approaches — marketing teams can remove a lot of speculation from their media planning and buying decisions with the help of artificial intelligence algorithms and machine learning.
This kind of aggregated data approach provides a more comprehensive picture of customers and their buying preferences and behavior, and it empowers faster, more informed decision-making by marketing teams. The speed and accuracy that data-driven approaches enable drives sizable ROI and can even suggest novel approaches and new marketing techniques.
The difference between data marketing and traditional marketing
Traditional marketing approaches are very different from data-driven strategies. Traditional methods often center around using physical assets such as billboards, flyers, and mailing combined with first-generation electronic media such as radio and television ads. Historically, these approaches were generalized and manual, aiming to reach as wide an audience as possible in the hopes of finding interest among the masses.
Traditional marketing campaigns and approaches are usually based on instincts and feelings, but little data. Guesswork, trial and error, assumptions, and out-of-date customer information are all attributes of traditional marketing. These components do yield some actionable data, but the picture they paint is murkier than the more comprehensive view that a newer, more informed approach can provide.
Data-driven marketing is a modern solution that offers valuable insights that weren’t available in the past. Data illuminates customer behaviors, demographics, purchasing history, and more, painting a powerful picture of the customer and guiding marketers to timely, personalized, and targeted strategies.
A data-driven approach with a 360-degree view in real time leads to higher customer acquisition and increased ROI. Indeed, the average ROI of a data-driven marketing campaign is about five to one.
The benefits of data-driven marketing
With such a dramatic ROI in comparison with traditional approaches, it’s easy to see that there are significant advantages to data-centric approaches. Understanding the potential gains of data-driven marketing and how they can help your team craft more effective campaigns pays real dividends.
Better clarity on the target audience
Seeing customers more clearly will give you valuable insights into what they want — and don’t want. When you have an accurate, detailed snapshot of your target audience, you can create and deliver relevant content at just the right time, in just the right way.
In today’s digital-first environment, every interaction a potential customer has with your brand can be tracked and analyzed. Prospects can be assigned a score based on the quality of those interactions as well as the likelihood of a purchase or other desirable next step in the customer journey. This process is called lead scoring and is another important advantage of knowing your audience.
In addition to mapping customers’ interactions with your brand, you should collect and analyze information that allows you to better segment your target audience. This information usually includes:
- Personal data such as name and address
- Engagement data like website and mobile app interactions
- Transactional data, including purchase history
- Attitudinal data like preferences and customer satisfaction
When combined and analyzed effectively, these separate pieces of information come together to provide a powerful snapshot of the customer.
Discover the best channels for promotion
In addition to providing clarity around your target audience’s needs and wants, data can also suggest the best method or medium to engage with that audience. For example, different age groups have demonstrated strong preferences for specific social media platforms — this information can help you target your approach on the right apps for that demographic.
Another example of a factor that can affect channel selection is location. Regional preferences combined with other demographic data can provide strong predictors around what products and services customers are likely to be most interested in — and on what channels. Location data can reveal proximity to a physical store, how long a customer spends at local events, and more. Aggregated with other predictive factors, location data can even help marketers guess where the prospect will go next — and which device or platform will be most effective in reaching them.
Relevant messaging through personalization
Personalization is a strategy that connects with customers to deliver direct, applicable messaging through a better understanding of what the customer wants. It uses real-time data to generate actionable insights around what messages and offers will be relevant to the customer.
Targeted, customized advertising works for many reasons. For one, misguided messaging can actually hurt sales — 74% of customers are irritated by irrelevant content from brands. Ineffective messaging like this is not only off-putting for the customer — it results in wasted time, money, and effort for marketing teams.
Data offers a holistic view of the target audience, including preferences and pain points, and a relevant strategy can be built with this information in mind. Personalized approaches include:
Recommendations of relevant products. Product recommendations that are well timed and germane to a customer’s needs are helpful. Personalized product placement yields higher sales and conversion rates.
Recommendations of personalized content. Guiding site visitors through the content funnel is an important step once you understand where they are on the customer journey. Companies can offer B2B customers tailored content recommendations no matter which stage they’re at. A content strategy can be informed by data from purchase, download, or search history. Demonstrating understanding of a customer’s needs in this way can help build vital trust and loyalty.
Customized landing pages and emails. Combining known data about the customer to make strategic decisions about landing page displays will help customers navigate sites more intuitively and move more quickly through the marketing funnel.
Tailored emails. Via email, marketers can customize content such as offers, images, videos, and messaging. Email is one of the most effective marketing tools when used in personalized campaigns.
Targeted social media advertising. Quizzes, videos, and brand messaging can all be personalized on social media platforms, and campaigns can be retargeted according to insights gleaned from data collection and analysis.
The challenges of data-driven marketing
The value of data-driven marketing is clear — a better understanding of the customer’s needs and wants often leads to more customized strategies, which in turn leads to significant increases in rates of purchase, loyalty, and ROI. But getting the right data — and understanding it in a way that yields smart strategies — can pose challenges.
Gathering the data
Collecting data is the first step in data-driven marketing, but it can be intimidating or confusing to gather data from website analytics, CRM, ecommerce tools, and other avenues. Here are some important considerations when gathering data:
Organization of approach matters. Even the best ideas need a good plan to be executed well. Identify your data collection objectives and sources of information and make sure you have the right tools to meet your objectives.
The timeliness of data makes a difference. Because much of commerce today is done digitally, consumers can interact with brands easily online through multiple channels. Tracking these interactions in near-real time gives marketers a strategic advantage — they can respond to opportunities when customers are in the right location or mood, instead of waiting until it’s too late to act.
Performance of data-gathering systems will affect outcomes. Older, outdated systems can lack the ability to gather relevant data in a timely way and may be missing data synchronization and bidirectional integration. Updating legacy systems or integrating existing systems with newer, more agile marketing tools helps ensure that data can be collected according to current best practices and modern capabilities.
Avoiding poor-quality data
Poor-quality data will form an inaccurate or outdated picture of the customer. Make sure that the data is accurate, timely, complete, and properly represents your target audience.
Identify which data needs to be included. Include only the data points that contribute meaningfully to the picture you’re trying to paint. Using too much data will make a customer view murkier, not clearer. Once you have a system that ensures data is clean and high quality, you can expand the number of sources you use.
Practice good data hygiene. Make sure you monitor and adhere to quality standards and put clear parameters around the lifespan of acceptable data. Marketing strategies based on obsolete data with incorrect contact or demographic information will produce bad results. Track the timestamp on collected data, define the lifespan of the data, and rank the data according to its accuracy.
Check your data sources regularly. Plan for regular reviews of where and how data is being pulled, and build a baseline so that aberrations and fluctuations can be compared against it. This kind of regular monitoring will allow errors to be identified quickly and keep problems small and manageable.
Pulling the data together
As we’ve laid out previously, data should be timely and as close to real time as possible. But pulling data regularly can be arduous, especially if you’re doing it manually — the more often data is required, the more chances there are of user error. The problem compounds the more complex the variety of data sources are, and the larger the volume of data that’s pulled.
When data is pulled regularly, fixing quality issues becomes an important and difficult task. Other issues such as data integration and preparation snags, scaling, data evaluation, and keeping costs and employee time expenditures reasonable also come into play.
Software like Adobe Real-Time Customer Data Platform can help by doing the heavy lifting of pulling data together. This powerful, feature-rich CDP collects and collates data into a standard taxonomy from multiple enterprise sources to create a fuller picture of the customer.
Overcoming data silos
When it comes to data-driven marketing, silos are bad news. Most data can be siloed in different platforms, applications, and even departments, but this separation comes at a cost — data needs to be integrated in order to best inform insightful marketing strategies. Siloed data limits the ability to fully understand an audience or have a big-picture view of campaign performance.
Real-Time CDP solves this problem by letting marketers combine data from all sources and systems — consumer and professional, internal and external, and both anonymous and known data. This unified data enables activated marketing strategies across channels and platforms in real time.
How to create a data-driven marketing strategy
The importance of using good data to better see the customer is clear, as are some of the top considerations for using a data-driven approach. Here are the first steps teams should take to craft campaigns using data insights.
1. Develop campaign objectives
Before you collect and organize the data, you need to determine what your objectives are for the campaign. What determines success? Who is the target audience? What is your ultimate goal? The answers to these questions will help you create a relevant, on-target strategy.
Campaign objectives should be SMART — that is, specific, measurable, achievable, realistic, and time-specific. Using these parameters will result in a strategy that is easy to track, adjust, and improve. A good way to start is to define aims in terms of sales goals, market shares, customer growth, price targets, website metrics, and social media engagement.
2. Compile the data
After your goals, success metrics, and overall campaign blueprint are established, it’s time to determine what data you need to make the campaign effective, and then start collecting it.
3. Build a team to analyze data
Creating an internal or external team to analyze and act on the data received is an important part of your data-driven campaign. There are many effective models to choose from — pick one that suits your business aims and available resources. Here are a few popular approaches:
Distributed team. This model functions in the way it sounds — instead of a top-down approach, experts are distributed across an organization, embedded in various teams. The approach seeks to understand the workings of a team in detail to meet its needs.
The center of excellence model. The leader (or team), assumed to be a subject matter expert in digital process and execution, builds the guidelines and processes for the campaign.
Hub and spoke. This model combines the strongest attributes of the previous two models and functions as a hybrid — there’s a center of command where ultimate decisions are made, in addition to experts distributed at a more local level.
4. Deploy the plan
Once the plan is developed, it should be implemented. Review the details of your plan and make sure your goals are realistic, then pull in the resources and processes needed to execute the project. Create workflows, assign roles, and put milestones and tasks on clear timelines with dependencies and backup strategies outlined.
5. Measure and track progress
During and after the marketing campaign, progress should be tracked so adjustments can be made and stakeholders notified. Tracked progress can be compiled into reports that include campaign metrics such as time spent, tasks completed, budget used, and any other scoping considerations, which can then be shared with interested parties. This information can be used to adjust tactics if goals aren’t being met.
Data-driven marketing tools
The right tools can make all the difference when it comes to building an efficient, effective marketing approach. Here are some of the best tools currently available:
- Google Analytics is a web service that tracks and reports site traffic for marketing and search engine optimization (SEO) purposes. It offers user behavior tracking, data reporting, customization, and more.
- Tableau is a big data analytics tool that was created to uncover patterns and trends in large amounts of data. It collects, processes, cleans, and analyzes data.
- BuzzSumo helps marketers discover targeted messaging, content, and placement opportunities in social media channels and search engines. It can help a campaign find new keywords, trending stories, customer questions, and track brand performance and engagement.
- Adobe Real-Time Customer Data Platform provides powerful data management capabilities that seamlessly combine known and unknown data to create one-to-one personalized experiences throughout the customer journey, across every channel and platform.
Get started today with data-driven marketing
Adobe Real-Time Customer Data Platform lets marketers collect, normalize, and govern B2B and B2C data and unify it into real-time profiles that can be activated across any channel.
Real-Time CDP combines the power of Adobe Experience Platform with robust data management capabilities usually reserved for IT departments. Real-Time CDP provides powerful information management capabilities that allow marketers to unify disparate data into a single format, gather and process information instantly, create real-time profiles and activation data, and generate actionable insights for B2B and B2C campaigns in a secure, compliant platform.