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What is Data-Driven Marketing

What is Data-Driven Marketing?

When marketing teams develop plans based on the study of big data, this is known as data-driven marketing. This research will reveal customer preferences as well as broader trends that can affect the success of a marketing campaign.

While a data-driven approach to marketing was historically uncommon, the proliferation of niche media outlets and changing customer expectations have made data analysis a necessary part of modern marketing strategies.

The massive amounts of data that corporations now have access to have supported a data-driven media planning approach. Marketing teams acquire data via apps and websites, and with excellent attribution modeling, they can follow each brand engagement throughout the consumer journey.

Marketing teams can see which creative assets produced more engagements, which channels gave the highest ROI, and more once all of this data has been parsed and analyzed. Organizations may fine-tune their efforts based on these insights to achieve the finest customer experiences and the most return on marketing expenditure.

The Benefits of Data-Driven Marketing

Consumers today are bombarded with brand marketing and message. As a result, they’ve grown more selective about which messages they’ll respond to. Marketing teams can dramatically enhance the chances that their target audience will click on their ad, join their webinar, read a blog post, or take any action that leads to a conversion objective when they use a data-driven strategy.

Data-driven tactics increase customer experience and brand perception by allowing businesses to better understand their customers’ requirements and desires. They also boost conversion rates since users are more inclined to pay attention to highly tailored messaging offered by data-driven marketing. The following are some of the most significant advantages of data-driven marketing:

Better Customer Experience

Data-driven marketing emphasizes the utilization of detailed consumer profiles to improve the customer experience. This is critical for success, as nearly half of customers say they will leave a website to buy a product somewhere else if they have a bad experience.

Data-driven marketing allows for more personalisation, which helps to develop trust between a consumer and a business while also providing great customer experiences. Consumer experience personalization can yield genuine returns, according to McKinsey, which found that individualized experiences can generate 5-8 times the ROI on marketing investment.

Better Attribution for Spend Optimization

Determining where their advertising budget is being squandered is a regular difficulty for marketers. Marketing teams can use data-driven marketing along with analytics tools to figure out which part of the advertising spend is having the most influence on conversions or brand awareness.

This is accomplished through the use of attribution models, such as unified marketing measurement, to assess customer journeys (UMM). To provide a holistic view of the path to purchase, UMM looks at multi-touch attribution and media mix modeling. Organizations can figure out what moves leads and consumers along the funnel and then budget accordingly.

Produce Relevant Content and Copy

Consumer data can be used to inform marketing teams about the types of creative, images, copy, and content that your target audience loves to engage with. Connecting with your customers requires sending the correct message at the right moment, one that caters to particular interests and adds value. Unfortunately, as two major data points show, many marketers struggle to align their content with their target audiences.

  • In the last five years, blog material has increased by 800%, yet social sharing has decreased by roughly 90%. This indicates that there is a misalignment between what brands say and what users value.
  • When they see ads from brands that they believe irrelevant, 74% of customers become irritated.

You may figure out what messaging and content pieces are resonating with your audience by digging into your analytics. This can help you make more informed product decisions and better understand your customers.

Better Decisions

Overall, a data-driven approach to marketing allows teams to make more informed decisions, with two out of three marketers saying that using data rather than gut impulses is preferred. Marketers can utilize data analysis to make decisions based on real-world use cases rather than theory.

Data-driven marketing, on the other hand, does not ignore the emotional factors that can influence a consumer’s purchasing choice. To guarantee that rational and emotional decision-making are correctly balanced in campaigns, marketing teams must examine data within a framework that considers both rational and emotional decision-making.

The Challenges of Data-Driven Marketing

Marketers and consumers alike will benefit from data-driven marketing initiatives. However, there are a few obstacles that can prevent marketers from fully utilizing their data or reaching out to clients in an effective manner.

Avoid Being Invasive

Consumers demand customized experiences, but they don’t want businesses to know everything about them. Even more importantly, if people want to share personal information, they want to know how it will be used to their advantage. Customers care about data openness, with 79 percent indicating they will cease doing business with a company if they realize their personal data is being used and acquired without their permission.

Companies should think about how they provide value to customers when using message or personalisation methods to target them. Consider the difference between making it easier for them to make purchases and showing them how much you know about them.

Furthermore, in light of legislation such as GDPR and CCPA, marketing teams must be extremely clear about how data is acquired and used, allowing consumers to opt out of data gathering.

Poor Data Quality

To have a data-driven plan, you must have the appropriate data procedures in place. This ensures that your decisions and strategies are based on high-quality data that is representative of your customers’ needs. If your data does not meet data quality criteria like timeliness, correctness, completeness, representativeness, and so on, you risk making decisions based on data that gives you little insight into your consumers’ true needs.

In reality, nearly half of all new data records have at least one major inaccuracy, and an HBR research found that only 3% of data quality scores are acceptable.

With this in mind, marketing teams must verify that data quality standards and regulations are in place before implementing data-driven methods.

Extracting the Right Information

Many companies are investing heavily in big data (sometimes millions of dollars), but have yet to see a clear return on their investment. If you’re collecting a lot of data but not the correct kind of data, it won’t help you plan your marketing approach. Despite the fact that 70% of marketing and sales executives consider data-driven marketing to be a critical effort, only around 2% of those who have invested in these solutions have experienced a favorable return on their investment.

Companies must have the right individuals, procedures, and infrastructure in place to make the most of their data.

This requires data scientists that can extract insights from enormous datasets, data cleaning techniques, and the appropriate software partners to filter, correlate, and process massive amounts of data.

It’s a result of having personnel with the necessary abilities and tools that helps them make the best judgments possible.

It’s Complicated

Implementing a data-driven marketing plan necessitates time and resources because marketing teams must guarantee that the appropriate policies and procedures are in place. While marketing teams often find the process difficult, the benefits are well worth the effort.

It might be tough to know where to begin, even if your organization has the necessary personnel and technology. Before going out, marketing teams should make sure they have a detailed plan in place, or work with a third-party team that can help them get the most out of their data.

Best Practices for Data-Driven Marketing

Consider the following when creating a plan to deploy data-driven marketing, particularly at a time when global data collection policies are getting more stringent (especially in terms of GDPR and CCPA).

Provide Value

The goal of data-driven marketing is to improve marketing success by enhancing the customer experience, which is made possible by data insights. The importance of the customer experience in this equation cannot be overstated. Every data-driven campaign should have a clear answer to the question, “What’s in it for the customer?”

With this in mind, simply developing a promotional sheet for your items will not be enough to stimulate downloads. Consider the user’s perspective and what they would find useful. What is the problem your customer is trying to solve based on the information you have? What stage of the buying process are they in? Determine the most useful piece of content or information you can supply from there.

Outline Clear Advantages

If consumers believe they will obtain better offers or more value from their brand interactions, they are more willing to provide personal information. Make it clear to clients that if they allow your company to utilize their data to create user profiles, they will receive something helpful. This might be in the form of individualized product suggestions or insider information in the form of a newsletter. Marketers must emphasize the benefits to customers.

Be Transparent

Many customers are concerned about how businesses use their data, which can range from intrusive messages to the risk of their data being stolen in a network breach. Marketing teams must be completely honest about the data they acquire, how they plan to utilize it, and how it will be preserved and secured.

Give customers the option of changing their info or deleting their account. GDPR and CCPA both need this. Marketing teams will be able to track and adjust data as desired by customers if they have a high level of visibility into where it is stored.

The Steps in Data-Driven Marketing

Implementing a data-driven marketing strategy might be difficult, as previously indicated. When a crucial step is neglected, this complexity is amplified, causing teams to backtrack and extend the program’s time to value. Review these crucial steps in the marketing process before you start, and make sure you have a plan and the resources you’ll need to fulfill each one.

Determine Which Data You Need

This will be determined by the program’s goal. If you’re seeking to create person-level user profiles, you’ll put a premium on gathering consumer data. Focus on attribution data if you’re trying to follow the path to purchase and customer journey. After you’ve decided on a target, make sure you’ve set KPIs that will allow you to assess the program’s success.

It’s critical to know what you’re trying to accomplish with the data. Work with your data science team to identify any gaps in your present dataset and determine how to close them in order to track KPIs and go forward.

Implement Data Quality Best Practices

You will not get favorable results if your data-driven program is based on erroneous or missing data. In fact, you risk altering advertising in ways that detract from the experience your customers desire. To reduce this risk, make sure you have clear data quality policies in place. This ensures that you’re making judgments based on the most up-to-date and representative facts. Establish policies across departments to guarantee that each team records the same data in the same format. The following are the most important data quality dimensions to consider:

  • Comprehensiveness
  • Consistency
  • Accuracy\Format\Timeframe
  • Validity
  • Integrity

Data-Driven Marketing Examples

Short-term performance programs and long-term brand building campaigns can both benefit from data-driven marketing. Here are a few examples of how marketing teams might use data into their plans:

Targeted Messaging

Attribution data can help your team figure out which sorts of message are most effective at attracting your target audience’s attention. This information is used to create user profiles, such as “responds to comedy in adverts” and so on. This type of material can be created by marketing teams, and AI-enabled systems can then provide it to the correct customer at the right moment, producing a tailored experience.

Better Branding

Marketing teams can better track brand creation activities via data gathering and analysis, which are vital yet tough to quantify. Organizations have more visibility into consumer values that they can speak to as a brand through branding initiatives. Customer retention and long-term growth are dependent on brand recognition and loyalty, but it can be difficult to demonstrate this ROI to stakeholders because they do not necessarily equate to a direct, quantitative sale.

Using data like leading indicators can assist marketing teams figure out what makes a brand resonate with customers and where they can improve their brand’s health quickly.

The Right Media Channels

Your role as a marketer is to find your target audience wherever they are. This may be on television or on Snapchat for millennials. This could appear in publications or newspapers for older generations. Understanding the subtleties of which channels to invest in for different audiences is critical to optimizing media spend. It guarantees the greatest number of engagements for the least amount of money.

Marketing teams can discover the highest-value channels by looking at how often an ad or asset was engaged with and how important that engagement was in pushing them along the sales funnel using attribution data.

The Right Time

Finally, use data and analytics to figure out when the optimal times are to execute your advertising. This is another another important aspect of tailoring your customer messages and optimizing spend. It responds to the query, “What time of day or week are your clients most receptive to advertisements?”

This could be during working hours for a B2B organization, when customers are actively looking for a business solution to a problem they’re having. For retailers, this may be the weekend before buyers intend to visit the mall for new seasonal fashions or to purchase on Black Friday.

You can better target potential consumers with information when they are ready to accept it by learning when they are most receptive to ads.

Consumer expectations today necessitate data-driven marketing, especially given the ever-increasing number of channels, applications, and devices via which to contact them. These plans, if followed, allow you to harness the potential of your data by personalizing consumer experiences, optimizing spend, and increasing ROI.

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