Two Strategies That Leverage Technology to Drive Referrals

Which one is right for your practice?

By Steve Stalzer, PT, MBA*

Advances in technology are helping many practice owners increase referrals and make better marketing investments.

Two strategies that have evolved recently as effective marketing methods are (1) utilization of claims data to analyze actual referral patterns in existing and new markets and (2) pay-per-click campaigns to drive new patients to your practice.

The purpose of this article is to provide an overview of these strategies to help determine if either is appropriate to grow your practice.

Claims Data & Referral Analytics

Imagine having a crystal ball that provided access to physician referral information within your market. What advantages could be gained by knowing where each physician referred his or her patients as well as the percentage of referrals by payer and by the affected part of the body. While you can use your electronic medical record (EMR) to access this data for your clinic, this crystal ball would allow you to access it for all outpatient clinics in your market.

As you have probably guessed, this level of data is available, and chances are, one of your competitors is using it today to gain a competitive advantage in marketing to physicians. Claims-based referral data can be used to strengthen your physician referral and relationship initiatives. By using referral data for the physician in your market, you can be more targeted in your approach by reaching out to the right physicians with whom to build relationships. Since you cannot reach all physicians in a market, nor should you want to, using data can help you understand which physicians represent the best opportunities for growth and relationship building. You can gain detailed insights into things like understanding physician alignment, knowing which physicians have growing businesses, and where there are opportunities to grow referrals.

Referral analytics allow owners to take a strategic approach in marketing to ideal referral sources. Knowing that 46 percent of a physician’s referrals to therapy are for shoulder injuries allows programs and messages to be customized. Claims data can also be used to target physicians who see patients with insurances that your clinic is in-network with and avoid those who see a high percentage of patients that are out of network.

Data can also be used to enhance success prior to opening a new clinic. By mapping physician referral patterns, you can better select locations for a new clinic based on actual referral data for nearby clinics. This provides firsthand knowledge of market dynamics and referral patterns before entering a new market.

Referral analytics can also be used in approaching a hospital regarding management agreements or joint ventures. By knowing referral patterns from hospital-employed physicians, one can make a compelling case to the health system for better management of therapy by using actual data on leakage and projecting the financial opportunity for such a contract.

If you want to maximize your marketing efforts or if you are planning a new clinic, referral analytics may be a great investment to ensure you maximize your return and give your team the best chance to exceed expectations.

Pay-Per-Click Campaigns

Pay-per-click (PPC) marketing is hardly a new strategy, but as people increasingly turn to the internet to search for therapy providers, this strategy is worth revisiting now more than ever, and can be one of the best marketing returns on investment (ROI) available to clinics today. As the name implies, pay per click is a model of internet marketing in which advertisers pay a fee each time one of their ads is clicked. PPC allows clinics to show targeted ads above the organic search results when specific keywords or phrases are searched.

Google Ads (formerly known as Google AdWords) is the single most popular PPC advertising system today. Each time a search is initiated, Google reviews the pool of advertisers and chooses a set of winners to appear in the valued ad space on its search results page. The “winners” are chosen based on an advertiser’s Ad Rank. Ad Rank is a metric calculated by multiplying two key factors: cost per click (CPC) (the highest amount an advertiser is willing to spend) and the quality score (a value that considers your click-through rate, relevance, and landing page quality). This system allows winning advertisers to reach potential customers at a cost that fits their budget.

To maximize PPC effectiveness, advertisers should consider enhancing keyword relevance, landing page quality, and the quality score. Crafting keywords is not as simple as listing “physical therapy near my town.” Keywords should be targeted, but early in a campaign, Google Ads managers may use broad search terms that produce high conversion rates.

Negative keywords can be used to reduce wasteful spending by preventing ads from showing up for nonrelevant searchers. A clinic may choose to list terms such as “chiropractic, equine, or psychological” to prevent ads from appearing for other forms of therapy. Frequent review of PPC campaigns helps to optimize spending and ROI by modifying ad text, extensions, and keywords as well as negative keywords.

Ben Holbrook, PPC specialist with 3 Plains Marketing, offers the following advice: “Before investing in a PPC campaign, it is wise to review landing pages, basic website appearance, and review your website’s call to action. An expensive PPC campaign will be ineffective if potential patients are confused or turned off by the appearance of your site. It’s important for visitors who click on ads to be taken to a landing page relevant to the term they searched. Quality score will be negatively affected, as well, if the content on your landing pages does not correspond with ad group keywords.”

Steve Stalzer, PT, MBA, is a PPS member and practice consultant with 8150 advisors. He has more than 20 years of experience in strategic growth, operational efficiency, and succession planning. Steve can be reached at steve@8150advisors.com.