InvestorPlace Media has built a strong subscription business in the competitive financial news industry by assembling a roster of stock market experts to provide advice and information. Their content includes more than 30 subscription products as well as free email newsletters, online content, webinars and books. Content is targeted for investors with a variety of investment strategies and styles.
InvestorPlace’s portfolio required some heavy lifting for Penny Lee, Director, Database Management, and her team. To segment lists and create targeted marketing campaigns, they had to deal with thousands of customer and prospect profiles from multiple data sources -- separate subscription lists, email opt-ins, ecommerce customers and website visitors.
“With the range of products we offer, our main challenge was that we couldn’t easily see who our subscribers were,” Lee says. “We couldn’t see what they responded to, what they were interested in.”
To better target their marketing campaigns, they needed a new way to analyze existing subscribers, website activity, email open and clickthrough rates, and other metrics. What’s more, they needed a better way to react to the daily swings of a stock market that influenced investors’ information needs. CAMPAIGN
Lee and her team developed an improved marketing strategy built on a new central database and new tools for the marketing team to analyze and segment lists and test new campaigns.
Here are five steps they took to integrate data and develop new analytics and testing techniques:
-> Step #1. Consolidate disparate sources into central database
First, Lee identified the sources that needed to be integrated into one database.
The team then fed all those data sources into one integrated database that created a “single-customer view” for each contact. That view shows which newsletters customers subscribe to, what email messages they respond to and what sections of the website they visit.
“I want to know who you are as an email address, but I also want to know what else you have done with us,” she says.
-> Step #2. Create tools to analyze list
Lee’s team developed new analysis tools that don’t require marketers to know database programming languages. A simple portal-style interface available on marketers’ computers, for instance, provides access to database analytics and campaign-planning applications.
Those applications can analyze all interactions with a given contact, such as their buying history and online behavior. Here’s how it works:
- Isolate date through query
A simple query process allows marketers to isolate data by clicking on tabs and folders that represent specific databases, product categories, and campaign performance reports. Some examples:
o Marketers can click on a folder representing a specific newsletter to call up the names of its subscribers.
o Folders containing reports from previous marketing campaigns let marketers search for contacts that opened or clicked on specific email promotions.
- Drag-and-drop function moves contacts
After opening each folder or report, marketers can use a mouse to drag contacts who meet their criteria into a separate workspace window.
- Visual elements show relationships
Elements in the workspace, such as Venn diagrams, which show all possible relationships between sets of contacts, help marketers identify targets that best fit the parameters of their queries.
An automatic-export function can move the final list of contacts into a campaign-planning application
-> Step #3. Develop targeted campaigns
The new database and analysis tools allow the marketing team to develop broad-based and smaller, more-targeted marketing campaigns based on specific stock market events, such as a rate cut by the Federal Reserve or a huge market swing.
“Whenever we have a market event, we have a group of advisers to promote,” says Lee. “There are some advisers we promote if the market goes down, or others to promote if the market goes up.”
For example, a market event that warranted special promotion of subscription products from one of their newsletter authors resulted in a campaign like this:
- Marketers started a query by pulling up names of subscribers who had already purchased a product from that author.
- They called up data from the Web analytics system showing which users had recently visited the author's section of the company’s website.
- They added prospects from the database who opened or clicked on email messages related to the author's investment advice.
- That list was checked against opt-in data to ensure that the company had permission to reach out to those prospects with special offers.
- Finally, marketers cross-checked their list against the list of names that were scheduled to receive a broad-based, corporate marketing message that day to ensure they didn’t receive competing offers.
With the list segmented according to those rules, the marketers then automatically launched the campaign from the central database.
-> Step #4. Identify variables for campaign tests
Lee’s team also began a series of tests that targeted specific campaign variables. The goal: refining marketing strategies even further.
For example, the team had never conducted much marketing right before Thanksgiving because of the constraints of a short work week. But they were curious about the potential impact of an offer timed for the long holiday weekend:
- The team created a special promotion specifically for the holiday weekend.
- They then segmented the marketing database based on purchase activity and email behavior.
Specific queries to find prospects included:
o Current or former subscribers of other related newsletters
o Recipients of free email newsletters related to the adviser's investing style who had clicked through to an article in the past three months
o Customers who had purchased a book by the newsletter’s author
- The campaign was timed to send three email messages over the course of the weekend.
-> Step #5. Track metrics and feed results back into database
For each campaign, the team tracks metrics to help refine strategy on an ongoing basis.
Key metrics tracked for each campaign include:
o Sales generated
o Unsubscribe rates
o Open rates
All metrics are fed back into the consolidated database and added to individual contacts’ profiles to help with future campaign targeting based on responses and behavior.
Consolidating data sources and developing new campaign targeting strategies has pushed the team’s marketing effectiveness to a higher level. InvestorPlace’s subscriber base grew 33% over 15 months after their new database marketing strategy was developed.
Lee’s team now has detailed insight into who their subscribers are and what messages they respond to -- particularly when marketing efforts add a new name to the database.
“What it helps us do is not just get a name, but continually to interact with that name and send them specific conversion messages,” she says. “We’re constantly re-engaging the customer.”
Another big factor in their success has been their ability to rapidly generate lists and launch campaigns. Database queries that used to take up to nine hours are done now in minutes. And the marketing team can turn around a campaign from concept to execution in three hours.
The ability to conduct more frequent and granular testing is also delivering more bucks to the bottom line. The team’s Thanksgiving weekend test, for instance, surprised everyone by generating $432,000 in sales.
“Evidently after people eat turkey and watch football, they want to buy investment newsletters,” says Lee. “That was a great weekend for us.”Useful links related to this article
Alterian - provided InvestorPlace’s database marketing software:
ARGI - performed the customization and integration with InvestorPlace’s existing infrastructure: