How to do Data Driven Marketing?
Data driven marketing from insights to actionData-Driven Marketing: From Insights to Action
What is data driven marketingWhat is data-driven marketing?
Data-driven marketing is a kind of marketing that incorporates digital analytics and data science in the decision-making process.
Data-driven marketing is a form of marketing that focuses on the use of data and insights to create value for companies.
This can take many forms, including predictive modeling, segmentation, A/B testing, and other forms of data analysis.
Data-driven marketing is about using data to help brands deliver the right message at the right time. For example, a company that does not have much in-house data but uses analytics from third parties may have a better chance of predicting which products will sell well.
The same thing applies to email campaigns: sending emails based on data gathered from past campaigns may be more effective than sending email blasts without any analytics behind them.
Data-driven marketing can also help with advertising decisions. With more information available about consumers’ preferences and behaviors, companies can choose where and how to advertise their products more effectively.
For example, if a company knows that consumers who purchase shoes tend to purchase other shoes within six weeks after their purchase, they could send an email offering 20 percent off when you buy another pair of shoes within six weeks.
How does it workHow does it work?
Data-driven marketing can be applied across industries. In retail, it can help retailers decide where to spend their budget on mobile advertising or digital display ads.
For example, if you know that women ages 25–34 make up 20% of your customer base, then you might put more emphasis on digital display ads for this age group than on traditional print ads (since most people are not using print channels for shopping).
Data can also help retailers decide when it’s beneficial to run special events such as in-store promotions or flash sales.
A data-driven media planning approach is now aided by the vast quantities of information that organizations have access to.
Marketing teams collect data through the use of applications or various websites, and with good attribution modeling, can track each brand interaction along the customer journey. When all of this information is parsed and analyzed, marketing teams can see which creative assets drove more engagements, which channels offered the highest ROI, and more.
Based on these findings, organizations can hone their campaigns to ensure the best customer experiences and the greatest return on marketing investment.
The benefits of data driven marketingThe Benefits of Data-Driven Marketing
Modern consumers are inundated with brand marketing and messaging. As a result, they have become increasingly discerning about which messaging they will engage with.
When using a data-driven strategy, marketing teams can drastically increase the chances that their target audience will 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, as they give 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 the attention of users. Some of the top benefits of data-driven marketing are:
Better customer experienceBetter 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 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 a consumer and brand while creating positive customer experiences.
Personalizing the experience for consumers can have real results, with McKinsey finding that personalized experiences can provide 5–8 times the ROI on marketing spend.
Better decisionsBetter Decisions
Overall, taking a data-driven approach to marketing 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 go into a consumer purchasing decision.
Marketing teams must evaluate data within a framework that considers rational and emotional decision-making to ensure they are balanced properly in campaigns.
The challenges of data driven marketingThe Challenges of Data-Driven Marketing
Data-driven marketing strategies stand to be positive for both marketers and consumers.
However, there are a few challenges that can keep marketers from extracting the full benefits of their data or from effectively reaching customers.
Avoid being invasiveAvoid Being Invasive
Though consumers want personalized experiences, they don’t want organizations to know everything about them.
Even more so, if they decide to give over personal information, they want to know how it will be used to their benefit. Consumers feel strongly about data transparency, with 79 percent of customers saying they will stop doing business with a company if they learn their data is used and collected without their knowledge.
When targeting customers with messaging or personalization tactics, companies should consider how they are providing value to a consumer. For example: making it easier for consumers to make purchases versus showing customers how much you know about them.
Furthermore, marketing teams must be incredibly transparent with how data is collected and used — giving consumers the ability to opt out of data collection, especially in light of regulations such as GDPR and CCPA.
Poor data qualityPoor Data Quality
To have a plan governed by data, you need to have the right data processes in place.
This will ensure you are basing decisions and strategy on high-quality data that is representative of customer needs.
If your data does not conform to data quality dimensions such as timeliness, accuracy, completeness, representativeness, etc., then you risk making decisions based on data that provides little visibility into your customers’ actual needs.
Almost half of new data records have at least one critical error in them and an HBR study could only loosely rate 3 percent of data quality scores to be acceptable.
With this in mind, before embarking on data-driven tactics, marketing teams must ensure they have data quality standards and policies in place.
Extracting the right informationExtracting the Right Information
Many companies are investing in big data (often spending millions), but have been unable to produce any tangible return on this investment.
If you are collecting large quantities of data — but not the right data — it will do little to inform your marketing strategy. 70 percent of marketing and sales executives have reported data-driven marketing as an important initiative, yet only about 2 percent have seen a positive impact when investing in these solutions.
To get the most out of their data, companies need to have the right personnel, policies, and infrastructure in place.
This means data scientists who can derive insights from large datasets, processes to keep data clean, and the right software partners to sort, correlate, and process immense quantities of data.
It’s a function of having employees with the right skills and software with the features to assist them in making the right decisions.
Its complicatedIt’s Complicated
Implementing a data-driven marketing strategy takes time and resources as marketing teams must ensure the right policies and controls are in place.
While marketing teams often find the process complicated, the returns are ultimately worth it.
Even if your company has the proper talent and technology in place, it can be difficult to understand where to start.
Marketing teams need to be sure they have an in-depth plan in place before setting out or should partner with a third-party team that can guide them on getting the most out of their data.
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