It may surprise you to discover that email campaigns remain the most effective marketing channel for many eCommerce businesses. According to McKinsey, email is 40 times more effective at acquiring new customers than both Facebook and Twitter combined, with customers three times as likely to make a purchase.
In the digital age, when everything is measured, we must ask ourselves: Are we measuring email campaign effectivity enough?
Marketing automation platforms such as Hubspot and Marketo measure email campaigns using traditional email marketing analytics metrics such as open rate, CTR (Click-through Rate), bounce rate, conversion, forwarding rates, and overall ROI. But while these metrics focus on the beginning of the customer journey, they fail to connect the dots to understand the bigger picture.
By integrating email campaign data with all other data sources, including events from web and mobile apps and CRM data, we gain a more complete understanding of the customer journey and deep insights into customer behavior from email campaigns — from the first click to their travel booking.
Finding the sweet spot: Optimizing the impact of each email
A leading business in the travel space concentrates its effort on email campaigns to effectively promote their offerings. Hubspot’s ability to collect traditional email data to measure clicks, open rates, and conversions was only the first step. To go beyond these traditional metrics, they needed to be able to answer the more complex business questions, such as:
– What times and regions are customers most likely to click and open their emails?
– What is the right number of emails to optimize my monthly engagement with customers?
– Which group of customers will potentially bring more value to my business?
Answering these questions require time-series behavioral analysis capabilities that gathers multiple data points into one. A more holistic analysis of the entire customer journey required integrating email campaign data with other data sources.
What is the optimal hour to send emails for best open rate?
To answer the question of when is the optimal hour of the day in different countries to send an email, we integrated email campaign data from Hubspot with raw historical event data. By querying and filtering data of email campaigns as far as 6 months back, we get the preferred time of the day for customers in each country.
Not a difficult question to ask your data, (using the right tools) but quite a useful insight to have for all future campaigns.
Adding the time dimension to email analytics
Examining the customer activities in relation to emails, over time, using time-series analysis, reveals fluctuations in customer actions, or behavior. For instance, examining open and click trends showed that people continue to open/click emails in the days after the email was sent. We learn that emails that were sent in a particular week in the winter for a warm beach vacation received a high response from Europeans even 14 days after the email was sent.
The segment of customers who opened the email 5 days after it was sent could be saved as a segment of “late openers.” This segment could be later targeted with optimally timed follow-up email campaigns.
These are the types of insights that provide great value in creating effective targeting and follow-up campaigns.
How many emails should be sent to customers to yield maximum engagement?
It’s a matter of hitting the sweet spot: too many emails and you’ll get customers to unsubscribe from your email campaigns; too few and you miss out on customer engagement. Does 7-10 emails sound too much? Well, the raw data tells a different story.
By querying email campaign data over time, businesses can see the magic number of emails they should send at any given month to maximize their open and click rates.
A conversion funnel between data points
What is the most popular conversion funnel that starts with an email open? What is the conversion rate from email to booking that occurs during the same day? Answering such questions becomes easy when your analytics gather data from different data points.
With advanced funnels, you’re not limited to predetermined steps or predefined goals. You can easily build any conversion funnel by examining any step of every event or property in the database, including email_open, booking_confirm, or booking value over 10$, regardless of the data source.
Such advanced funnel analysis leads to data-driven marketing actions by targeting any user behavior segment created from the funnel. For instance, you could target the particular segment of customers from a certain country who arrived at the payment page in that same session and dropped off at the payment page, the last point in the conversion funnel.
To ensure that only the most valuable customers are being targeted, businesses could focus only on sending certain last-minute promotions to customers who have previously booked a trip 12 hours before their flight.
Email marketing data combined with web and mobile user behavior data
One of the best ways of having an edge over your competition in eCommerce is by better understanding your customer journey and behavior. Traditional email marketing and even marketing automation systems give you some insight, but take you only so far. Businesses who want to understand what happens to their customers after they leave the email ecosystem should consider integrating their existing system with Cooladata to gain these vital insights into their customer behavior over time. All of these insights are available on a single dashboard so you can react quickly to any sudden changes in your customer email engagement. For businesses focusing on customer acquisition, conversion and growth mainly through email, the types of insights above are priceless.
Want to gain insights from all your data? Learn more about our data integrations.