Knowledge-based marketing: Future of healthcare marketing

Dr Aanshu Sharma & Dr Biswendu Bardhan

In today's age, every consumer wants to be served according to his or her unique and individual needs. Oganisations have also geared up to provide customised solutions, tailoring their services/ products based on actual customer preferences, rather than on generalised assumptions. Hence all the businesses are exploiting the information systems and technology to accumulate huge amounts of customer data, as they understand that the knowledge in these huge databases is important to gain competitive advantage and support various organisational decisions. There is a great need of a well-defined, simple but integrated system to extract the knowledge of the customers from these huge databases and then to apply this knowledge for making various critical decisions, particularly marketing decisions.

The healthcare market is no different, where a great deal of information is available from the transaction databases (every point of service utilisation) and from customer/corporate (health-seeker) databases. This great wealth of database gets unutilised and thus wasted due to the lack of appropriate tools and techniques required for the analysis. Hence, database marketing in healthcare sector is characterised by marketing strategies linked to knowledge-based marketing which uses appropriate tools for searching and analysing customer data in order to find implicit, but potentially useful information, thus revealing previously unknown patterns and ultimately comprehensible information. These tools are called Data Mining Tools, like statistical analysis, graphic visualisation, decision trees, etc.

These tools help in profiling the consumer/customer (health seeker), profiling the variation/deviations in transaction and finally analysing the trend.

Profiling the consumer/customer

A hospital seeks to decide on the right strategies to market its services, on the basis of the profile of the health seeker. Hence an appropriate model of the health seeker is the first step. This entails information regarding the demographic profile along with the health seeking behavior mapping. The Data Mining Tools can be extremely helpful in this situation.

Frequency of facility/service utilisation

Mapping the number of times service provider/hospital is visited, and revisited, the particular facility/service utilised by the health seeker; thus building on the various promotional tools and consumer-oriented programme, clubbing of frequently availed relevant services, age-wise service clubbing, etc. Revisits can be utilised to promote a loyalty Programme.

Service utilisation in the recent past

This is to map the number of times the services have been utilised in the recent past and to understand the reason of non-utilisation of services, if any. Similarly, the mapping can be used for a group of health seekers (like corporate) to understand their pattern of facility/ service utilisation. The programme can thus be tailored as per the specific needs.

Identifying and isolating consumer / health seeker groups

This can be done by concept description (grouping customers based on the domain knowledge and the database) and by class description (clustering the health seekers according to attribute similarity and conceptual cohesiveness). This can be elicited by the following example.

Health seekers falling in the category of 'eligible couple' can be provided packages for genetic counseling/ education regarding contraception/reproductive health education/screening for various relevant diseases/ services provided by the hospital for obstetric care and family planning. Similarly, packages can be provided for corporate group having similar demographic and occupational characteristics.

Prospecting

The profiling of health seekers gives valuable indication to the service provider on prospective consumers. For instance, in the above examples, the 'eligible couple' group can be targeted for providing paediatric services/immunisation services and so on. The corporate can also be looked into in the same manner.

Statistical analysis of the various promotional tools can be carried out to see the success or failure of the above promotional programme. The short term as well as long term effects of the programme can be measured by seeing the pattern of health seeking behavior. This can be the basis for evaluating the value added to the health seeker's life.

Profiling the variation/deviations in transaction

A deviation can be an anomaly, a change, even a fraud, and in healthcare scenario it could signal an impending disease outbreak. The knowledge of these deviations is important to the health service provider, more so is the timely knowledge and initiation of relevant actions. For example, more than normal utilisation of a particular facility/service could be seasonal variation or changing lifestyle of a particular stratum of society or could be an environmental influence resulting in the deviation. The deviation can be within the service provider's own infrastructure. For instance, comparing a group of customer care personnel and identifying those who stand apart from the average in solving the patients' problems either in a positive or a negative way.

The change in the behavior of a health seeker or the provider's internal customer can provide us with the opportunity to detect and classify such deviations, and further information should be collected, if necessary. Any price change or promotional programme can also be viewed in the perspective of deviation it caused and the changes can then be queried.

Analysing the trend

Trends are patterns that exist over a period of time. Trends can be long-term trends like slow but sustained growth of health check facility utilisation following continuous community/corporate health education programme initiated by the service provider (hospital). Trends could be short-term, like sudden increase in the number of Gastroenterology cases during monsoon or sudden increase or decrease in the surgical cases during different periods of the year. Our Data Mining Tools, especially data visualisation, allows us to view complex patterns as visual objects in three dimension and colours.

It can further be used in association with other Data Mining Tools, like concept description and deviation detection to explore the knowledge in database. Similarly, graph-based technique or other geometric projection techniques can be used to even detect hidden and subtle trends in the database.

Data mining tools also provide statistical tools to precisely measure the performance of various parameters. Trends can be used to forecast future utilisation patterns. Service providers are interested in knowing the effect of various marketing programmes on the utilisation rate. These tools help in detecting the relationship between a particular programme and the profile of the health seeker (or if any change is detected in the profile).

In the current scenario, all the programmes are customer focussed. Hence, all the steps targeted towards the Customer Relationship Management should be based on identifying the right customer, differentiating among them (classification), interacting with them to learn from them and finally customising the services/facility to the needs of the customers.

Inadequate knowledge about customers and the lack of systematic knowledge management framework hinders the organisational efforts to manage their much-valued customers (health seekers).

In the current customer-centric and customer-driven business scenario, there is a need for furthering our understanding of the use of various tools required for searching and analysing data and for a proper knowledge management.

Dr Bardhan is a consultant with Novella HMS and Dr Aanshu Sharma is a marketing executive at Lilavati Hospital.