09 Aug. 2018 | Comments (0)
The 2018 Excellence in New Communications Awards were presented at a dinner and gala in New York City in June. The full case studies are published in the latest SNCR 2020 paper, which you can download for free here. Below, we feature the winning case study from AMN Healthcare.
The issue being addressed
AMN Healthcare provides hospitals and healthcare facilities with access to the industry’s largest network of qualified clinicians in the country, including travel nurses, travel allied healthcare professionals, and locum tenens physicians.
Prior to 2017, AMN’s candidate attraction and sourcing activities encompassed marketing to specialty-based RNs with messaging about the appeal of travel nursing, with an approach of contacting all candidates without knowledge of those most likely to work and/or provide greatest lifetime value. Our digital marketing team marketed the travel nursing lifestyle to candidates without knowing life circumstances such as age, urbanicity, marital status, presence of children in the household, and other factors which significantly influence one’s likelihood of pursuing and accepting travel healthcare opportunities. We were developing marketing content throughout our channels that spoke to our audience as if they were all motivated by the same thing and in the same point of the candidate lifecycle. While we had evidence that this persona interested in the travel lifestyle exists and is likely to go on travel assignments, based on the number of clinicians on assignment we knew this persona did not represent the majority of our traveling clinicians. What we lacked was the ability to further identify the candidate’s motivators, life circumstances, and key attributes to better match their wants to our career choices.
Further, knowing that travel nursing has been a viable career opportunity for more than 30 years, we sought to understand some of our theories around clinicians’ interests in this type of career. Our questions included: Why are some providers motivated by travel, while others are motivated to stay close to the town where they grew up? Why are some new parents willing to travel for work with their young children, while others are not? We knew we needed to understand the “why” to develop a more segmented and personalized approach for our target audience.
In 2017, AMN’s candidate sourcing and digital marketing team sought to more clearly define our target audience and in doing so, lower acquisition costs while increasing the supply of candidates in our sales funnel. Most importantly, we hoped that deeper insight into our target audience would enable AMN Healthcare to more effectively match clinicians with the best assignments for them, in the right location, at the right time, resulting in a better customer experience. While understanding households, personas, and clinician information is not new, we believe our approach of matching household data to careers was a new approach that we did not see exhibited elsewhere and provides a unique new approach to one of the most important milestones in a person’s life—making a career choice. The activities outlined in this application have revolutionized the ways in which AMN Healthcare attracts and retains its healthcare professionals.
The target audience
Our target audience for this approach is nurse and allied health professionals who are more apt to work as travel clinicians based on our candidate intelligence. Utilizing household data on all US households and distilled down to 15,000 predictive variables matched to our candidate historical data, we focused on ideal segments of clinicians most likely to work as travel clinicians. We segmented our target audience into distinctive groups utilizing weighted, segmented data based on AMN’s historical data of candidates likely to place, coupled with key behavioral and demographic factors provided by our data partner. We then developed custom personas representative of clinicians most likely to work travel assignments.
Our two-part solution for acquiring data-driven insights and applying them to our daily sales and marketing activities entailed:
- Developing marketing personas; and
- Developing a system for scoring, ranking, and prioritizing leads for the sales, recruitment, and marketing team as well as for our clients.
Marketing personas To more thoroughly understand the healthcare professionals we were targeting, we constructed personas, which are detailed profiles based on a combination of demographic, psychographic, and behavioral data. These personas clearly illustrate who our healthcare candidates are, which pain points and motivators they share, and which offerings they care about the most. While many companies use marketing personas to better relate to their customers, AMN’s personas are unique because they include detailed, data-based insight into candidate’s career motivators. Knowing more about our personas’ attitudes towards work has enabled us to identify which factors are most important to them in a travel assignment. We can then speak to these factors on our calls with them and in our digital marketing content.
Lead scoring system Our team ideated and implemented a lead ranking system, which categorizes and ranks leads based on their likelihood of going on a travel assignment. We used predictive analytics to determine which qualities make certain healthcare professionals more likely to go on a travel assignment with AMN. This was a new approach providing consistency of information and our approach to how best to speak to and motivate candidates. Prior to this approach, decisions on candidate prioritization and attraction methods had been based on imperfect data to qualify and prioritize a candidate lead. As a result of our new automated lead scoring system, our recruiting staff who engage with leads at the very beginning of the sales funnel now know which leads to prioritize through our new data-driven approach to segmenting, scoring, and prioritizing leads for the recruitment and sales teams. We established expected conversion rates and have witnessed success in 2017 using this new method.
An automated process When our CRM receives a new lead record, it delivers a data signal to our data partner whose system processes the record and identifies the persona of the individual and attaches a score. This information is then processed into to our CRM in real-time. While this is happening, our system also classifies the lead and assigns it a classification code. This automated process of assigning every lead a persona and classification code is used by the frontline recruitment team to prioritize calls and customize their conversations to the clinicians they speak with. The digital marketing team uses the personas and coding system to develop persona-specific content and campaigns through lead nurture tracks, emails, social, web content, and other channels.
- Accurately determine lead quality and focus marketing and recruiting efforts on those most likely to convert
- Utilize newfound candidate intelligence to personalize and prioritize communication with the highest-opportunity candidates
- Understand more about our clinician’s wants and expectations to improve the candidate experience
- Create cost savings and efficiency
The solution deployment
This initiative was multifaceted; several departments and technological tools were involved in the development of our data-driven lead classification and prioritization system. AMN’s marketing, IT, and recruiting departments worked together to synchronize and integrate our candidate intelligence into our business processes.
This was the first time AMN had implemented real-time coding of data for a systematic, comprehensive, and data-driven approach to scoring leads. One challenge we faced was ensuring company adoption of our newfound candidate intelligence and prioritization process. To simplify our highly-detailed candidate information into a useable tool for recruiters, we created a classification code. Every lead is assigned a code, which takes three high-level data points into consideration: third-party data from our candidate intelligence vendor, conversion likelihood, and the first-touch channel (website, referral, social media, etc.) from which the lead originated. The end result is a prioritization code that recruiters can refer to when deciding who to call first.
In addition, every lead is classified as a specific persona, which recruiters use as a reference point to personalize their conversations with candidates. A single, 26-year-old millennial nurse without children has significantly different needs and expectations for her travel assignment than a mature mother who is taking care of her aging parents while also paying for her children’s college tuition. This new system has enabled us to prioritize candidates who are most likely to convert and speak to them, whether on the phone or through digital marketing messaging, in a way that is likely to be more relevant to them.
Below is a summary of how AMN used deeper candidate insight to personalize its traditional and non-digital sales and marketing communications:
- Developed persona-based sales materials for recruiters:
- Phone scripts for each persona
- Persona one-sheets outlining demographics, psychographics, and motivators
- Trained junior recruiters on personas for more personalized phone conversations with candidates
- Trained junior recruiters on lead codes for call prioritization
- Use candidate intelligence vendor’s CRM complete service to obtain missing contact information of leads in our database
- Deployed 180+ email campaigns, testing different content and messaging to determine what resonated most with personas
- Tailored imagery and messaging of websites and paid social media ads to personas.
Measures of success
The personalized approach to marketing outlined in this application has revolutionized AMN’s approach to attracting and retaining healthcare professionals. This approach has resulted in higher candidate engagement, more conversions, and lower acquisition costs.
- Increased candidate engagement Developing data-based marketing personas was a critical step toward ensuring our content would resonate with our audience. Marketing personas have helped our marketing, sales, and recruiting teams internalize AMN’s ideal customers and better relate to them. This heightened awareness of our customer has enabled more personalized calls with candidates, more relevant digital marketing content, and a greater ability to find assignments that are the best match for our clinicians. Personas have enabled AMN to communicate to audiences in a new way, and we have seen an increase in candidate engagement, acquisition, and retention. Specific examples of increased engagement:
- Persona Facebook ads outperform generic ads; click volume is 13 percent higher on average.
- Persona emails outperform generic emails; open rates have been 33 percent higher and click volume has increased by 40 percent.
- Higher conversion rates Thanks to our lead prioritization system, which we developed in-house at AMN, our digital marketing team is now able to identify and target the clinicians who are most likely to convert. As a result, recruiters are receiving a higher quantity of high-quality leads and prioritizing them over others. We now see that the highest-value candidates convert at a higher rate. Following are specific examples of higher conversion rates:
- We have seen a 278 percent increase in conversions from email. For one email campaign in particular, we generated 189 monthly placements from a personalized email, compared to 50 monthly placements from the prior generic email.
- High quality leads now convert at a higher rate. Compared to 41 percent previously, 50 percent of the highest-quality leads now convert. The conversion rate for our highest-opportunity candidates has increased by 2 percentage points or 16 percent.
- Client sales leveraged candidate intelligence from our project to close a $12M MSP client. This client had never worked with AMN before, but they viewed our candidate insight as a “game changer” and were eager to sign. The contracting process from initial presentation to close was unusually short—six weeks compared to the typical 11-week average.
- Cost savings and efficiency AMN can now accurately determine the quality of a lead. Because we can predict who is most likely to convert to a worker, we can focus our sales and marketing resources on the highest-opportunity leads. Specific examples of cost savings and efficiency:
- Paid advertising costs have decreased by as much as 32 percent during our initial test period.
- We have seen higher conversion rates without a significant change in costs. For the higher conversion rates mentioned above, implementation costs remained relatively unchanged.
Recruiters now have a data-driven prioritization system at their fingertips, which enables them to spend time and effort on calling and working with leads who are most likely to convert. The company saw a 16 percent increase in application conversions in 2017.