First, let us start by explaining what is data-driven marketing?
The process by which marketers obtain trends and meaningful insights by analyzing market data or company generated data and then further translating these meaningful insights into actionable decisions based on numbers is called data-driven marketing.
The primary goal of data-driven marketing is to optimize strategies and processes which caters the trends and unique demands of customers by leveraging data to gain deeper insight into what customers want.
When companies truly understand the why, who, what, when, and where customers are interacting with their sales and marketing efforts, only then they can make better decisions about everything, from customization and personalization to the timing which caters specific segment of audiences.
Now, let us discuss the challenges of data-driven marketing?
It is quite obvious that the process of data-driven marketing works on the use of data. Using insights in the decision making processes to make marketing decisions can come at the expense of creativity, depending on how marketers choose to leverage data derived insights.
Marketers cannot maximize their ROI and even get their analysis correct if they are using incomplete or old data.
Example; Your sales or marketing department is planning a campaign and acquired a targeted list of companies. Now, Mark who is a CEO at ABC Corporation, imagine a situation where your email goes to the inbox, only later you find out that Mark left the job 6 months ago. It can put significant damp in your marketing campaigns when you have a large number of contacts who are like Mike.
Just imagine, how frustrating it would be when you have the correct email addresses and you find out the person is no longer employed with ABC Corporation. The person has left the organization 6 months ago but the company decides to keep the email address active. The loss of your resources would increase by 30% of the contacts in your data those have left the company 6-11 months ago. In such case, your analytics would show such details for contacts who are no longer there!
Let’s take another example; your sales or marketing department is planning another campaign to be sent to your existing subscribers, but one of your contact named Zack who is a CMO at XYZ Corporation has not opened or shown any engagements to your emails in the last 3 months. Now, consider the situation when you have a significant number of people on your subscriber list who are not interacting with your email at all. Do you really know if he is employed with that company or not? The insight data which you will receive by sending the campaign to such list won’t be effective and you cannot make any decisions to optimize the campaigns which improves your ROI.
For such complex conditions, Infotanks media has been constantly working to manually verify each contact through social and other online sources to validate the existence of contacts in the company. However, our email delivery rates would be more than 90% and we guarantee that contact is also working in the company.
Now Imagine, an ideal scenario where you have 100% validated contacts to analyze your data trends and make informed decisions. Hitting the ideal scenario could be a hard sell but you can get close to ideal scenario, depending on how you use this data.
The Final Conclusion:
The key to success in data-driven marketing is to plan, test, analyze, repeat and then redeploy after you have obtained significant insight which informs you about your course of action. Use A/B testing and other methods as well to see what works best for you by comparing it to your original KPIs.
Data is driving majority of the marketing decisions being made in this highly competitive world. If you are not leveraging data to inform decision making and derive marketing insight, you are falling behind and we do hope to see you around.