With the average person receiving over 2,900 marketing messages a day, consumers have grown accustomed to a barrage of marketing messaging during their daily routines. Most of these messages are ignored, especially if they’re not relevant to the recipient.
To increase the probability of engagement, many hospitals and healthcare organizations are using multi-channel approaches – a combination of digital and traditional channels to optimize initial outreach, drive long-term engagement, and convert leads.
Digital options, such as email marketing, are an undeniably cost-effective way of reaching consumers and moving them through the sales funnel. However, the most successful marketers complement those messages with targeted traditional marketing efforts. Direct mail is one of the most common – and effective – methods used in the healthcare industry. Why? Because direct mail marketing simply works.
However, given the time it takes to create, print, and send direct mail, it can be expensive. To optimize results and generate ROI, marketers need to be sure that direct mail is being sent to the best prospects. In this effort, propensity modeling can be a valuable tool.
In this post, we’ll explore how leveraging propensity models can provide specific insights into consumers and patients, and how to utilize that data to optimize direct mail campaigns.
Direct Mail in the Healthcare Landscape
Healthcare marketers have a wide variety of digital tools at their disposal to target and market to consumers. However, in an internal study of customers, we found that when direct mail is used alongside digital advertising it can yield statistically significantly higher response conversion rates above single channel alone. It’s no wonder why, either. In today’s digital age, direct mail has several unique benefits:
- It’s personal: Given the effort needed to develop printed collateral, successful marketers know that for the best ROI, smaller, personalized batches of direct mail work best. In addition, when the messaging between channels is aligned, conversions and response rates are further increased. Healthcare marketers can leverage multiple data sources (names, interests, and sociodemographic information) to provide individualized content.
- It’s tangible: There’s something to be said about being able to look and touch a piece of content. In fact, when people can touch and see a piece of content, consumers are more likely to engage with and remember that content.
- It generates high ROI: Across industries, every $167 advertisers spent on direct marketing last year, made $2,095—a 1,300 percent return.
In order to improve direct mail results, the first step is to develop a target audience for the marketing campaign as a whole. Enter propensity modeling.
How Propensity Modeling is used in Marketing Campaigns
Propensity modeling uses analytics to organize data, identifying patterns and relationships to distill unique insights on specific targets. A target is an empirically defined “group” – in this case, patients who have had specific clinical services. The primary goal of multivariate propensity models is to find those patients and non-patients that look most like those who have already had the service or procedure. Marketers use propensity model scores, as well as additional analytics and data to find the best prospects.
The data used to develop a propensity model may include diagnostic data, visit history, sociodemographic info, age, lifestyle, personal preferences, and interests. With analytics, this information is used to develop a model – a set of indicators (multivariate) – that statistically make it possible to identify prospects that need a specific procedure, appointments, or services in the near future.
Using propensity models with a healthcare CRM, marketers can create a segmented list or targeted audience to inform and optimize a hospital’s marketing campaign strategy across multiple channels. Marketers should take their time in defining their campaign audiences; in our experience, the more work done upfront in planning translates to better campaign results. As mentioned earlier, the elements selected using propensity modeling and other analytics can be used for direct mail, email, digital and other campaign channels.
Applying Propensity Models to Drive Direct Mail Conversions
It takes multiple touch points to earn a customer – some studies put it as high as 18 to 20 – but direct mail can be the closer that leads to a conversion. Here’s a look at the steps necessary to apply propensity models to optimize direct mail results:
Define your goals: In order to leverage propensity modeling to its full extent, marketers need to clearly define both their overall campaign goals as well as the individual sub-goals for each channel, including direct mail. Operational definitions are those that are measurable – a critical piece of defining goals. Are you trying to cross-sell, upsell and retain existing patients, or acquire new ones? The better defined your target goals are, the more effectively you can customize your efforts to assist in campaign success.
Map out your campaign: After defining campaign goals and determining that direct mail marketing can assist in driving conversions, you’ll want to define your media mix and allocate your budget based on the propensity model. For example, if you’re using a mix of email, paid advertising, and direct mail marketing, you’ll use a wider, less targeted audience for digital channels and drive traffic to campaign landing pages. Due to expense, a segmented audience of the best prospects as determined by the propensity model can be targeted for direct mail.
A large part of mapping new and concurrent campaigns is to leverage existing and past campaign information. Know what has worked and not worked, and leverage what has been shown to be related to campaign response and conversion rates.
For example, if the primary campaign objective is to increase knee replacement surgeries, you can segment your leads to focus on patients or consumers who have a higher likelihood to need a knee replacement, are within a target age group, and are located within a general proximity of hospitals that perform knee replacements.
The best performing group may get four pieces of direct mail, the next set receives three pieces, and so on, as the budget allows. The number of touch points should increase based on audience performance.
Personalize your messaging: Once you’ve defined your audiences, you can personalize the individual messages of your direct mail to cater to their unique propensity model data. By including a lead’s name, interests, and relevant healthcare data, you provide a personal experience that helps move leads further down the funnel. Remember, channel alignment is the use of the same elements across multiple channels in the same campaign.
For example, if your primary goal is to promote a health and wellness program, but a number of leads are also indicating that they have or are at risk of developing diabetes, you can tailor your messaging to promote your overall campaign goal of boosting health and wellness program participation, while also offering resources that cater to their propensity for needing diabetes-related services.
Measure campaign success: Once your campaign is live, it’s important to track, measure, and analyze the effectiveness of direct mail (and all channels) and whether the propensity model and additional concurrent analytics are driving results. Use this information to adjust the current campaign or inform future marketing campaigns.
For healthcare marketers looking to drive campaign success, direct mail is a great option to add to the mix, especially within multi-channel initiatives. To increase the probability that direct mail will generate high ROI, marketers need to take the time to develop a specific, targeted audience. By leveraging propensity modeling, as well as other analytics, marketers can achieve this specific audience targeting while also using that information to personalize their direct mail content for a bigger impact.