Product & Service Marketing

Transform Product & Service Marketing with TigerGraph

Business Challenge
Traditional Solutions
Referral Relationship
Ranking the Influence
Community Detection
Business Challenge
Marketing a new product or service is getting more complex every year with the proliferation of digital channels, shrinking attention span for consumers and businesses alike and lack of trust in all direct advertising messages. Marketing professionals estimated that over 26% of the marketing budget would be lost as a result of poor strategic planning and/or incorrect channel focus.
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Cost of developing new products and services escalates every year, with each new drug costing the pharmaceutical industry over 2.6 Billion US dollars. Marketing to the hubs of influence works very well - 92% of the marketers who used influencer marketing found it effective. Influencer marketing shows up in all spheres of life from buying a Coach purse for your daughter because her favorite YouTube personality carries it or switching to a new cholesterol or blood pressure management drug because your trusted cardiologist recommended it over the current one due to higher efficacy. The main challenge for the marketers is finding these hubs of influence, understanding the community attached to each hub and prioritizing the marketing activities to effectively launch the new product or service through the hubs.
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Traditional Solutions Are missing the Mark
Finding hubs of influence on the social media channels (Instagram, YouTube, Twitter, Facebook etc.) is well understood and there are a plethora of tools that can identify the hubs, characterize the communities or audience attached to each hub and rate the relative value of each community for consumer product marketing.
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For more complex products such as new pharmaceutical drugs (for e.g. PCSK9 inhibitor cholesterol drug), equipment (for e.g. higher resolution X-Ray or MRI) or healthcare treatments (for e.g. TAVR, the minimally invasive heart valve replacement treatment), identifying hubs of influencers among physicians and other healthcare providers requires deep analysis of patient claims data to uncover the referral relationships. Traditional analytics solutions built on relational databases require expensive joins among large tables containing prescriber, claims and patient data. It can take hours, sometimes days to complete the database joins and that makes traditional analytics solutions unsuitable for this type of analysis.
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Why TigerGraph, a Native Parallel Graph Database for Product & Service Marketing?
Uncover Referral Relationships with Deep Link Analytics
Uncovering referral relationships is a lot easier in Tigergraph, as the patient, prescriber and claims data is pre-connected in the graph database. Consider the example, where Dr. Douglas Thomas, a general practitioner sees a patient, p1003 on Sept 8, 2017, for shortness of breath symptom resulting in the claim c10005. The same patient, p1003 sees Dr. Helen Su, an interventional cardiologist (surgeon) on Sept 20 for Cardiac Catheterization or Angiography (claim c10030) and again on Sept 23 for the Angioplasty operation (claim c10031).
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TigerGraph visually shows all of these claims connected with the patient and the prescribers in the GraphStudio so that data analysts can understand the relationship intuitively. TigerGraph also links them based on a time window to deduce referral relationship. In this example, the claims occurring within four weeks are considered for establishing a referral relationship. It takes four hops or steps for traversing from the referring physician, Dr. Douglas Thomas to the referred physician, Dr. Helen Su via relevant claims identifying 3 common patients, p1003, p1004 and p1005 over the month of August and September. A referral edge or relationship is established between Dr. Douglas Thomas and Dr. Helen Su and the relationship edge carries important information such as the number of patients referred, healthcare condition groups related to the referred patients. The prescription claim data can be added in, to provide specific drugs for Cardiac care that are frequently prescribed by both physicians. Armed with these insights, pharmaceutical companies producing the cardiac care medication and the medical equipment manufacturers producing stents and other products for the cardiac surgery can market those products to Dr. Douglas Thomas and his referral network including Dr. Helen Su for the San Jose healthcare market.
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Ranking the Influence by Hubs with Graph Algorithms
After establishing the referral relationships among influencers or trusted product or service providers (such as prescribers or doctors in case of pharmaceutical and healthcare industry), next step involves identifying the most influential hubs driving most activity such as healthcare claims for a specific condition such as cardiac care or diabetes management). Graph algorithm, PageRank is often used for this purpose. Consider the example, where Dr. Douglas Thomas, the general practitioner is driving referrals for cardiac care issues to three surgeons - Dr. Helen Su, Dr.
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Rick Summers, Dr. Zane Adams and two cardiologists - Dr. Henry Chang and Dr. Neil Patel. Dr. Don Kirk is another physician in the area, driving referrals to two surgeons - Dr. Helen Su & Dr. Rick Summers and one cardiologist - Dr. Larry Ko. Graph Algorithm, PageRank creates a unique ranking for each physician and Dr. Douglas Thomas with the PageRank of 3.9 is the most influential physician driving referrals for cardiac care in the area. Dr. Don Kirk is the second most influential physician with PageRank of 2.5.
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Community Detection Around the Most Influential Hubs
After identifying and ranking the hubs for their influence with PageRank, the final step in the product and service marketing driven by influencers is to identify the community around each hub and evaluate the market opportunity to determine the relative importance of each community. TigerGraph’s open source graph algorithm library includes the community detection algorithm to identify communities around each hub. Consider the example where there are three communities of connected prescribers and patients identified for East San Jose for treating cardiovascular disease and providing preventive care with medicines to manage hypertension.
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Community id 70163044 is for Dr. Douglas Thomas, Dr. Don Kirk, and their referral physician network and their patients. TigerGraph’s high performance SQL-like graph query language, GSQL is used to aggregate the spend across all claims for the community that is related to the cardiovascular disease, along with insurance payouts as well as the out of pocket cost for patients. Total spend along with insurance payouts and out of pocket cost is calculated for the hypertension medication prescriptions. Armed with these insights, pharmaceutical companies producing the hypertension medication and the medical equipment manufacturers producing stents and other products for the cardiac surgery can prioritize visits to the most influential hubs in communities with the maximum spend on those products or services in the east San Jose healthcare market. This delivers the new innovations in medicine as well as healthcare instruments and procedures to the community that is likely to benefit most from it while delivering maximum revenue uplift for the producers of these products and services.
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Getting started with TigerGraph