Ecommerce stores generate an enormous volume of data every day. Even the amount of customer information stored by a single company is often too large to be analyzed and interpreted by a person who lacks adequate training. Whereas not drawing accurate conclusions from the data renders the results of multi-channel marketing automation largely accidental.
From this article you will learn:
- What types of data are used in marketing automation.
- How customer data can be used in marketing campaigns,
- How to draw accurate conclusions by analyzing these data.
Success measured by data
Peter Drucker, a world-renowned management expert, once said that if you cannot measure something, you will not be able to improve it either. Applying it to the marketing campaigns management: if you do not collect data on marketing activities, forget about improving KPIs – and this should be the goal of every person responsible for marketing in the company.
Contact information such as email address and phone number aside, what data should be collected then, to optimize KPIs and drive the campaign management mechanisms?
1. Demographic data
These are basic information about the recipients of your communication, usually collected when they sign up for a newsletter – online or at a customer service point (most often in a store or a service outlet). The data is in large part provided by the recipients themselves – for instance age, gender or address.
2. Behavioral data
In multi-channel marketing automation behavioral data includes all information about how the recipients of the communication behave. This information can be tracked, aggregated, and then utilized in a completely different channel from the one that was used to obtain the data. The information provides, in the first place, the details on the open and click rates of messages, as well as the data regarding purchases in the online store, describing website or social media traffic.
The recipients preferences are very often overlooked and not assigned to a particular category. In fact, this information has the biggest impact on maximizing the campaign results.
The purpose of collecting data
Since you have such a wide spectrum of data on the recipients of your marketing communication at your disposal, there are three main ways in which you can use them.
How to use customer data in the marketing communication
Segmentation. In other words, defining the target group for a specific message. Well-designed segmentation should take into account demographics (women/men), behavioral data (which users in the online store visited product category X) and preferences (which customers want to receive weekly product recommendations).
Personalization. The purpose of a personalized marketing message is, first and foremost, to incite the recipient’s interest in the offer by creating the feeling the brand knows them well enough. While it’s a standard practice nowadays to display the name in an e-mail or SMS message and goes unnoticed, displaying a web push reminder about unfinished purchase which includes the products from the abandoned cart can incite to complete the transaction.
Automation. Having compared the data gathered via different channels you may find that one of them generated more sales that the others. You should consider attributing sales to individual channels per customer segment as soon as at the stage of planning the automation paths. For example: if you have information that the email channel brings you 25% more conversions after the first message than the SMS, then you should focus more on the email.
However, in order to effectively use customer data in the automation process, you need to take a step back and understand which information is the most important for your business.
Practical insight into the data
As mentioned in the beginning, it is not enough to know what kind of data you can collect and how to use it in your marketing automation activities. You need to understand this data to achieve the KPIs set not relying on sheer luck, but as a result of conscious actions.
3 steps to understanding the data
Analysing the behavior
The first step to understanding the data is behavior analysis. At this stage have a look at:
- How many recipients open your messages?
- How many clicks in the links are there?
- Which links are clicked?
- When is your online store most often visited?
- On average, how many people unsubscribe from each campaign?
- At what time of day are the most sales recorded in the online store?
Analysing the campaign results
The same applies to the data that you need to interpret at the second stage – analyzing the results of the campaign. Check, among other things:
- How many conversions a given campaign generated?
- What was the ROI of this campaign?
- What is the average profit per campaign?
- What is the average profit per recipient?
- How many new leads did you manage to acquire thanks to the campaign?
Senior executives in the company will be particularly interested in the answers to these questions. CMO will not be interested in the fact that the link in the web push notification has been clicked 1,000 times, but in how much money you have earned thanks to these clicks.
Analysing the motivation
The last stage is the analysis of the motivation. Some of the questions you need to ask yourself are:
- Why does a given channel generate bigger ROI than others?
- Why are there trends and fluctuations in the campaign engagement indicators?
- What makes the customers unsubscribe or abandon their purchase in your online store?
- Why does a particular channel generate more subscriptions than others?
- What causes that the customers acquired via a given channel abandon shopping carts more than the others?
Once you learn what makes the campaigns a success or a failure, you’ll be able to improve them effectively.
The data you collect, as well as its categories, may differ, depending on the nature of your business. The way you are going to analyze them is also your individual choice. The common goal of all businesses, though, is to understand why certain actions pay off and what can be done to achieve the results that meet our expectations. Multi-channel marketing automation platforms make it easier not only to analyze the data, but also enable you to create automation paths, which analyze and use the available subscriber data at any stage. Knowing what data to focus on and how to analyze it will help you achieve better (and better) results. Good luck!