Introduction:

Don’t flounder making quality marketing decisions; use data. Data can help you find the best opportunities, make accurate decisions and wisely spend your money where you will get the biggest bang for your buck. We have compiled these articles to show you how data is being used today in marketing.

What is Data-driven Marketing?

^[1]Data-driven marketing is the strategy of using customer information for optimal and targeted media buying and creative messaging. It is one of the most transformational changes in digital advertising that has ever occurred.

The rising quality and quantity of marketing data have been followed by explosive growth in creative production and automation technologies. These burgeoning mar-tech and ad-tech sectors now enable the personalization of every aspect of the marketing experience.

Data-driven decision-making answers questions like who, when, where, and what message and makes those answers actionable.

Usage and activation of data, often in an automated or semi-automated manner, allows for a significantly more optimized media and creative strategy. This people-first marketing strategy is more personalized. It has also been responsible for driving considerable R.O.I.s for marketers.

^[2]Why Is Data-Driven Marketing Important?

There’s no question that people have preferences that guide their thinking and behaviour. Therefore, a company that caters to those preferences has a far better chance of converting prospects into paying customers.

For example, a lawn-mowing company sends postcards seeking new customers to an entire metro area but gets less than 1% response. Fewer than 5% of those become new customers. Deciding that data-driven marketing might improve those results, the company studies demographics and discovers a regional area where homeowner income falls 10% to 30% below the median income for the overall metro area. Another postcard campaign to that region that stresses low prices for lawn service produces six times the number of new customers. That second campaign used data-driven marketing to focus on what homeowners in that region found most important.

Using such a data-driven marketing approach can give companies a snapshot of their customers’ buying habits. With that understanding, businesses can tailor their sales and marketing strategies to those customers. In addition, data-driven marketing sources can include basic personal information such as age, income level, marital status, number and ages of children, birthdays and other demographics.

How Do Marketers Use Data to Identify Goals?

In general, the high-level goal of marketing is to create customers and deliver products and services at a profit. However, every marketing campaign needs to have a plan. It might be a revenue target, a count of units sold, a count of new customers acquired, and so on. Failing to set a goal for each campaign leaves doubt as to what the campaign accomplished.

Marketers can use data-driven marketing insights to establish goals by tapping into various data sources. In the B2C marketplace, for example, these can include demographics, psychographics, big data from social media, C.E.S. (customer effort scores), NPS® (Net Promoter Scores), and others. Studying such data can reveal segments of an overall population that have similar preferences, behaviours or inclinations. Understanding those helps marketers refine their messaging and their offers to most closely fit such segments. That process clarifies the establishment of goals.

For instance, you might set a campaign goal to find three essential explanations that cause customers to hold negative attitudes toward the company or its products. Then, you might choose to contact a target audience consisting of people who completed a Net Promoter Score survey as “detractors” or “passives” — that is, from those who were not favourably disposed toward the company or its products. Having such data on customers allows marketers to define campaigns they otherwise would have no way of implementing.

How Is the Data Used?

Savvy marketers using data-driven marketing have found many ways to use the data that underlies their marketing efforts. A few examples…

• Suppose you’re running marketing campaigns on a variety of channels. In that case, data can identify which channel is performing best at which stage in the funnel with marketing attribution solutions.
• The Weather Channel sells ad space to companies by analyzing the geographic location of 3 million website visitors. Companies can buy ad space for targeted audiences. For example, shampoo companies that sell “anti-frizz” formulations can directly target prospects in humid climates.
• Netflix and its streaming video competitors and companies like Spotify suggest movies and music based on recommendation engines that analyze past customer preferences.
• Walmart wanted to understand better what consumers are trying to find when they search the Walmart website. Search inquiries are composed of data. Using A.I. and machine learning, the company analyzed that data to present products that are most likely being sought. It’s led to a 10% to 15% increase in conversion rate.
• Because automobiles are increasingly connected to the cloud, they send large volumes of data back to auto manufacturers every day. Using behavioural prediction technology, that data can reveal the personal experiences of car owners. Therefore, dealerships mining that data can offer customers unique, personalized experiences and predict with great accuracy when one is likely to buy a new car.

Implementing a Data-Driven Marketing Strategy

Marketing experts largely agree on the steps needed to implement a successful data-driven marketing strategy. The topics below represent the steps those leaders and marketing analysts consider essential.

1. Identify the goals you wish to achieve with a data-driven marketing strategy. Many recommend using the S.M.A.R.T. method where your goals are: Specific — Rather than “increase” revenue, use a specific target: “increase revenue by 12%.”Measurable — They must be reducible to a numberAchievable — Goals must be attainable. Otherwise, they serve no purpose.Relevant — Meeting the goal must benefit the company in some fashion.

   Timely — Set a reasonable deadline for meeting every goal.

2. Decide what kind of goals you want to establish. These could refer to attracting new customers, revenue, profits, enhancing customer experience, and combining these and others.
3. Build a team that will have the skills necessary to analyze the data you collect. For example, it should incorporate people from various departments — sales, I.T., marketing, and customer service — to build a cross-disciplinary team.
4. Build your buyers’ personas.
5. Decide what data you need. Depending on the goals for a given campaign, you may want to look at the time visitors spend on a web page, their browsing data, social media interactions, data captured by CRM, survey results and more.
6. Automate your workflow. The amount of data available exceeds the ability of most teams to process and gain insightful perspectives. Choose the automation tools that work with the kind of data you collect.
7. Collect your data, whether it’s coming in real-time, from a third-party data broker or another source.
8. Then, use the automation tools you’ve selected to analyze the data.
9. From that analysis, choose the channels you’ll use to run your campaign. For example, you might select P.P.C. ads, email marketing, content marketing or any method compatible with your needs.
10. Finally, launch your campaign. Monitor the results, calculate your R.O.I., then take what you’ve learned to improve the next iteration.

^[3]The Benefits of Data-Driven Marketing

Modern consumers are inundated with brand marketing and messaging. As a result, they have become increasingly discerning of which messaging they will engage with. When using a data-driven strategy, marketing teams can drastically increase their target audience’s chances to click on their ad, join their webinar, read a blog post, or perform another action that drives a conversion goal.

Data-driven strategies improve customer experience and brand perception, giving organizations an understanding of consumer needs and interests. They also improve conversion rates because the highly targeted messaging enabled by data-driven marketing is more likely to catch users’ attention. Some of the top benefits of data-driven marketing are:

Better Customer Experience

Data-driven marketing focuses on using in-depth consumer profiles to make the customer experience better. This is essential to success, as almost half of the consumers report leaving a website to purchase a product elsewhere due to a poor experience.

The added personalization afforded by data-driven marketing builds trust between consumers and brands while creating positive customer experiences. Moreover, personalizing the experience for consumers can have actual results, with McKinsey finding that personalized experiences can provide 5-8 times the R.O.I. on marketing spend.

Better Attribution for Spend Optimization

A common challenge for marketers is determining where their advertising budget is being wasted. Data-driven marketing-led analytics tools allow marketing teams to discover which portion of the advertising budget has the most significant impact on conversions or brand awareness. This is done by evaluating customer journeys using attribution models, such as unified marketing measurement (UMM). UMM looks at multi-touch attribution and media mix modelling to provide a comprehensive view of the path to purchase. As a result, organizations can determine what moves prospects and customers down the funnel then allocate dollars accordingly.

Produce Relevant Content and Copy

Evaluating consumer data gives marketing teams insight into the types of creative, visuals, copy, and content that your target audience prefers to engage with. Delivering the right message – one that caters to personal interests and creates value – at the right time is essential to connecting with your consumers. Unfortunately, many marketers struggle to align their content with their audience, as evidenced by two key data points:

• • Blog content has increased by 800 percent in the past five years, but social sharing is down by nearly 90 percent. This means there is a disconnect between what brands are saying and what users find valuable.
  • Seventy-four percent of consumers feel annoyed when seeing ads that they find irrelevant from brands.

By diving into your analytics, you can find what messaging, and content pieces resonate with your audience. This can lead to more effective product decisions and help you understand your clients.

Better Decisions

Overall, a data-driven marketing approach allows teams to make more informed decisions, with 2 out of 3 marketers agreeing that it is preferable to base decisions on data than gut instincts. Data analysis allows marketers to make choices based on real-world use cases instead of theories. However, data-driven marketing does not discount the emotional considerations that can influence a consumer’s purchasing decision. Therefore, marketing teams must evaluate data within a framework that considers rational and dynamic decision-making to ensure they are correctly balanced in campaigns.

Conclusion:

Article Compiled by hughesagency.ca

Article Reference Links:

1. https://www.makethunder.com/data-driven-marketing-definition-examples/ ↑
2. https://www.demandjump.com/blog/what-is-data-driven-marketing ↑
3. https://www.marketingevolution.com/marketing-essentials/data-driven-marketing ↑