To improve subscriber and user experiences, financial content website Investopedia decided to combine its six newsletters — all of which required manual template editing and content selection — and combined them into one automated, behavior-driven send.
In this case study, read how revamping their newsletter gave the Investopedia team a 114% increase in pageviews year-over-year.
Investopedia is a financial content website that's designed for all level of investors, from active traders to financial advisors to novices and students, according to Janine Silva, Director of Email Marketing and Integrated Marketing, Investopedia.
“We're really focused on providing our audience with actionable financial insights of all types, either connecting them with a financial advisor about a question they might have, or providing a term for a class that they might be taking in grad school,” she said.
No matter what their level of expertise, “we're really looking to provide people with the financial education and information that they need,” she said.
The marketing team at Investopedia had a change of focus in their content strategy and felt it was an opportunity to align the newsletter strategy.
“We really have focused a lot of our energy on providing insights around the current marketplace, the current political climate, the current economic climate and digesting that for our readers,” Silva said.
Instead of having many verticalized newsletters in very niche and specific topics, the team decided to focus their energy on two goals.
“The first goal being that we want to support this new content strategy and really provide our editorial voice to our newsletter products. And the second goal [is] to provide our readers with information that they're the most interested in on a really one-to-one level,” she said.
They felt this was an opportunity to get away from the “one-size-fits-all, batch-and-blast approach, and really send an email that's specific to a user,” she said.
“About a year ago, I had conceptualized this idea but knew that we had a lot of groundwork to do to get it going,” Silva said.
First of all, there was a need to create relevancy about aligning marketing efforts with content, she said. That means finding a clear editorial voice that marketing can support.
Then, she said, find ways to “refine that side of the newsletters to make sure that we're really providing distinct products and offerings in our newsletters.”
“We took six newsletters and rolled them into one [My Investopedia newsletter], mainly because the editorial burden of curating and picking that content day in and day out gets really redundant sometimes … when you slice a topic like finance into so many thin pieces,” Silva said.
It wasn’t just a matter of alleviating an editorial burden. “I just really felt strongly that it would be a better user experience [while] also maintaining the newsletters that we as a company felt strongly about, and keep them editorial,” she added.
Alongside the My Investopedia newsletter, the team still has morning and evening newsletters with information and news that investors need to know.
To get the newsletter going, the team began a complete overhaul of the metadata and tagging structure of the CMS system. This helped to organize and categorize their content correctly.
That process took a while, she said, because “we're a site that's been around for 15 years. We've had tons of freelancers and editors and contributors and writers who have had totally different approaches to how we tag and organize and identify2+3 our content. We really had to start from the ground up in rebuilding that data.”
Step #1. Align teams with organizational structure
Investopedia is in a unique place, Silva said, because “teams work really easily together. There's tons of collaboration. So, it's certainly not hard to find the buy-in from other teams like product or editorial or marketing. We all are in it together.”
She said that they also have the luxury of having “really smart data scientists on our team. They did a lot of the heavy lifting as far as, ‘What is this piece of content about? How do we tag it?’”
With the data team working on streamlining the tagging system, the editorial staff received training on the organizational process. Also, they made sure the system was structured so that it alleviated some of the manual process — which eliminated some manual errors.
Getting the brand’s email service provider involved was vital as well, she added. Its system ingested the data around Investopedia’s tagging structure and content. The team then leveraged the ESP’s algorithm to provide personalized content for an individual subscriber.
“Cleaning up the data that goes into that algorithm has really shown great success,” she said. “I think when we initially started, it became clear that our data going in wasn't that great. So, we had to refine and improve it so that [our ESP’s] algorithm could work to the best of its ability.”
Refining that data using a better structure involved categorizing content — but not manually.
“Instead of manually tagging a piece of content with tags, we use a product that we've built in-house that extracts words or tags about a piece of content to say, ‘Okay, I'm looking at this piece of content and there are four instances of 401(k). This piece of content is probably about 401(k), and it probably belongs in the retirement channel,’” Silva said.
With that new set of data, those tags then are applied to an email subscriber.
“If I'm on Investopedia reading a piece of content around 401(k), now 401(k) is applied to my profile that says, ‘This is what I'm interested in.’ So, we're building these user profiles based on their behavior,” she said. 0
The combinations of topics, she added, are almost limitless, because customer’s interests come in limitless combinations.
“We’re all complex individuals … ‘Yes, I'm interested in retirement, but also I read about Tesla, and I'm also a novice investor looking to gain ground in my investment knowledge,’” she said.
The brand does have typical personas that fall within their range of customers — people who are interested in personal finance, finance professionals, financial advisors looking to continue their knowledge or advance their career and even high net worth individuals who are looking for the best ways to invest their money.
Previously, as a reader, “you would have received a combination of six newsletters around specific topics. So, you might have received a retirement newsletter. You might have received a personal finance newsletter. You might have received an ETF investing newsletter — all really specific niche financial topics,” she said.
Each one of those newsletters had its own cadence, Silva added, and the team manually curated content for each one.
Now, they roll all of those newsletters or topics together into a product they call My Investopedia. Based on a subscriber or user’s behavior, as well as the popularity of the piece, a subscriber’s My Investopedia newsletter will be filled with content covering as many topics as the reader is interested in.
“My newsletter will be filled with content that I could have previously been receiving in the verticalized newsletters, but now it's all wrapped into one. So, on any given day, I could be receiving a newsletter that is covering a breadth of content,” she said.
Step #2. Run tests on data combinations
Starting in December, This whole process took six months to roll out, Silva said, because the team had to do the tagging structure and taxonomy work, but also because they began to run tests on the feed and the combinations of data going into it.
“At first, we started with only pieces of content that had been published or republished in the last week. Then we realized we have this huge library of evergreen content that is sometimes difficult, as an editor, to surface to people — but as a reader, is very beneficial,” she added.
Silva said that the team then changed the feed to be evergreen — but to also include recent pieces of content. Weighting then, became a question with the team asking, “Are we going to weight recency more than popularity?”
The team ran A/B tests to answer questions that were coming up as they moved further into this process. They began by testing to see if combining all newsletters into one Investopedia newsletter would be worth it.
“People who continued to receive that mix of newsletters — standalone newsletters around topics —that was our control group; they just stayed the course,” she said. “We also took another group — we rolled all of their newsletters and interests into this My Investopedia and gave them that newsletter.”
After running it, they continued to tweak it with a series of follow up tests — such as running it for different periods of time to validate.
“It was a constant tweaking of finding the right combination of data points to then really find the sweet spot. The results are astonishing. We've seen over 100% lift in pageviews [and an] 81% lift in unique sessions,” Silva said.
Customers seem to be responding to the change, she added, based on the metrics they have seen.
“Nobody seems to be outraged, which I sort of find as a really great sign. I think that, a lot of times, when you make those changes, you cross your fingers and hope that [subscribers] don't come after us for this,” she said.
Now that the newsletter has been running for six months, Silva and her team are going to look at the data to do a retention analysis.
“How did people who were new — who had never received the old way — do, as far as retention? How have we improved, compared to the old way, to really see the lift? I'd like to think that we're going to see a really significant lift, especially based on the sort of lift in traffic that we've seen and have had that sustained,” she said.
Step #3. Focus on user experience
“I’m pretty strong about user experience, and we really tried to communicate to people this is the change that we're making — This is how you can update your preferences. If you'd rather not receive this, this is how you stop receiving it,” Silva said.
Being upfront with customers about exactly what was going to change in the newsletter — was key.
“I think our customers appreciate that, and I only say that based on the fact that they don't unsubscribe,” she said.
In a world where our data is being used for us all the time, she added, “if you're upfront about it as a brand to say, ‘Your behavior is going to influence this and it's going to make a better product for you,’ people are more receptive to that than having data used sneakily in the background.”
At the beginning of this process, the team sent out the newsletter with a paragraph at the top explaining what the changes were and how it affected them.
“We also used the subject line to attract people to open that newsletter to say, ‘Hey, we've made some changes. Here's the latest and greatest content that we still are providing you. This is how it will be from now on. This is how you manage your preferences. This is how you make your own experience better,’” she said.
Evolve the newsletter customization process
There are currently two ways to get this personalized newsletter, Silva said. One way is to just subscribe — at first, the team won't have any interest data — but as the subscriber comes onto the site and gets the newsletter, their interest graph will change. Thus, the content will change.
“We'll serve the most popular pieces of content to begin with, and over time, it will improve [to relevant content],” she said.
The second way is to allow people to self-select topics they're interested in.
“If you're on a term page that's an investing term, you can subscribe to the topic of investing. Similarly, if you're on a Roth IRA term, you can subscribe to the topic retirement,” she said.
The Investopedia newsletter has evolved in two ways, she added, where they’re taking data based on what a subscriber specifically wants, but also taking into account that subscriber’s actual behavior.
“I always use this example, but I think people do different things than what they say they're going to do — I say that I eat healthy, but if you handed me a menu and it had fried chicken on it, I'm going to order fried chicken,” she said.
It’s important to find the right blend of what people say they want and what they actually want — based on their behavior, Silva said.
“Yes, people are saying they're interested in this and we should honor that, but also, they're saying they're interested in something else — based on their behavior,” she said.
Decision-making can be overwhelming, she said, and with all of Investopedia’s content offering, “it’s hard to know what you want. If you sign up for too many, it can be too much. We want to avoid that kind of experience.”
“Your output data is only going to be as good as what you put in,” Silva said. “For us, that was a new taxonomy and tagging structure to our content. Personalization and any sort of AI automation is never going to work unless you have clean data going in.”
From this newsletter personalization change, the team has seen a 114% lift in pageviews year-over-year — as well as an 81% lift in unique sessions.
A product that has grown out of this effort has been a watch list that is now on the Investopedia site.
“It allows users to self-select tickers or companies that they're interested in following. They can change that at any time, and we provide them with the content that's relevant to that ticker,” she said.
If subscribers choose Tesla, Amazon or Apple, for example, they will receive a newsletter with information about those stocks.
“I think that's also in line with delivering content to people that's actionable. They can then take action, learn about it and understand the possibility for their investments,” she said.
That product has grown out of the knowledge that if they transparently collect behavioral data on subscribers and users — and in turn provide a better experience — people will appreciate that.
“I really feel strongly … about telling people exactly how their data is being used. I think being upfront is refreshing. I think a lot of brands don't do that. I think that [decision] allows users to trust a brand; it allows users to take action if they want to, and hopefully, we'll see, when we do the analysis, that it will lead to retention,” she concluded.
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