E-commerce marketing automation is often being thought of as synonymous to artificial intelligence, clever neural networks, evaluating an endless number of probable outcomes in order to market your products to your customers in such a way that they will buy more from you.
Well, that’s not exactly how marketing automation works, even though it’s not that far off.
Marketing automation uses datasets such as customers’ in-store purchases and their online behavior in order to help build marketers understanding on how their customers interact with the brand.
This allows marketers to view the data in the broader context and setup scenarios (conditional marketing campaigns) which help them to contextualize their offer based on customers’ interactions.
This leads a meaningful dialogue between brands and their customers even at on a large scale across multiple channels.
In short marketing automation:
- Helps marketers to gain insights from data
- Adds context to marketing communication at scale
The first, arguably the most important, pillar of e-commerce marketing automation is data management.
Data management means that marketers are able to import datasets into the marketing automation tool and connect them using a common unique key which identifies the same customers across within the dataset in order to contextualize their behavior.
When setting up your marketing automation platform, you may want to connect personal and demographic data, online behavioral data, engagement data and transactional data, so you will be able to get the most concise understanding of your customers’ interactions with your brand.
The next pillar of marketing automation is customer analytics. Your e-commerce marketing automation platform should be able to provide you with a detailed set of reporting options in order to get the insights you need to understand your customers.
In order to be able to get the insights you require to run your automated marketing campaigns, your tool should be able to support you with the capabilities to perform advanced calculations and operations in chronological sequence.
As for the reporting tools, the ability to visualize and report the data as a flow, funnel or in a simple table with charting options is the pure minimum, but for e-commerce analytics, you should be looking for a platform which will help you to perform geographical, trend and cohort analyses as well.
The lifeblood of marketing automation lies in the ability to design scenarios. It’s usually a visual representation of what must happen in order to trigger marketing communication with a customer.
Scenarios are often represented like flowcharts with nodes indicating a certain action such as filtering certain customers, sending them messages over email or SMS or defining a dynamic time of communication based on each individual customer preferences.
A Practical Example Of Marketing Automation
Customer, let’s call her Simona, visits your brick and mortar store, buys a new purple dress and after a few days, she visits your online store.
Your marketing scenario will kick in, because it was able to match and recognize her previous purchase and how long ago it was.
Your marketing automation platform then calculates the probability of what Simona may be looking for and what would fit her well with her previous purchase. It also takes into consideration the products that you need to sell as soon as possible, so you won’t risk overstock.
Simona doesn’t need to search through thousands of products on your store, she immediately gets what she wants. Both of you are happy since she bought something, she loves and you made a sale.
That’s the power of marketing automation.