Across every industry, our clients say they need to respond more quickly and effectively to changes in customer needs, global markets and crises such as pandemics or natural disasters. To do so, they need to more quickly integrate and access quality data from inside and outside the business.
Many are also discovering that the anonymized data insights they generate can be monetized, either by selling it to others or using it to improve their own business. For example, a lessor of commercial trucks may need externally sourced data about population growth and manufacturing and shipping trends to decide how many and which types of vehicles to buy and where to locate them.
But the company can also sell the data it generates about the performance, fuel economy and reliability of its trucks to the truck manufacturers to drive improvements, or to providers of repair services to help them stock parts and offer preventive maintenance.
However, the existing processes for finding, integrating and accessing this data often take far too long, as they require the negotiation of complex licensing agreements and the creation of custom integration and validation scripts for each new data source.
Turning to data marketplaces
Data marketplaces ease these problems by providing centralized sources for cleansed, standardized data. Demand drivers for data marketplaces include:
- Marketers who need information about the identity, needs, shopping habits and experiences of customers. With such data, they can increase marketing efficiency, guide product development, personalize offers and adjust pricing and delivery channels to maximize market share and profits.
- Logistics managers who need the latest information about raw materials availability and supply chain bottlenecks. This data can help them get the right raw materials to the right facilities, and get finished products to the right markets at the lowest possible cost.
- Marketers who want third-party demographic, purchase intent and product/brand affinity data to personalize the customer experience by promoting the right products and services at the right time.
- Life sciences companies that can use third-party physician ratings, credentialing and public health data to identify healthcare providers in their efforts to target potential customers.
- Insurers looking to reduce their risk exposure through timely, comprehensive and secure access to third-party data about macro- and microeconomic, geopolitical, climate and social events.
Third-party data at work: Insurance underwriting and risk evaluation
We worked with a major US property and casualty insurer to develop a data marketplace to improve the efficiency, effectiveness and profitability of its underwriting.
The insurer sought to consolidate all its third-party data in a central repository that could be shared seamlessly across the organization. Among other uses, the company sought to better understand the risks of insuring applicants by using third-party data to predict the likelihood of a fire in a home if a member of the household smokes, as well as emerging risks such as property damage due to fracking.
However, the accuracy and speed of its underwriting were limited because the third-party data was updated only once a week and needed to be cleansed to ensure its consistency and quality. In roughly eight weeks — about 80% faster than existing processes — we helped the insurer ingest data from three external sources, converted the raw hierarchical data into multiple flat tables, enabled an internal data hub using the Snowflake Data Exchange, retrieved data from the data exchange into users’ accounts and joined it with existing operational data.
This sped the insurer’s risk analysis and underwriting decisions, allowing it to make faster and more profitable policy offers to customers. The data marketplace also allowed it to increase its book of business by identifying potential opportunities, such as coverage gaps or a rising number of employees at a potential customer.
A data-infused recipe for market relevancy and advantage
Our success creating an internal data marketplace for this insurer — and other companies with which we’ve worked — rested on speeding two critical processes: third-party data integration and governance.
- Integration: This refers to the gathering, combining, cleansing and presentation of data from multiple sources. While the data from each source may be correct, there may be inconsistencies among the data sources in how they define or present, say, the name of a provider or their account number. This can require lengthy and costly data cleansing.
For the insurer, we used the Snowflake Data Platform and metadata — data about the data — to eliminate inconsistencies and add insurance-specific data quality rulesets to make publishable on the data exchange.
- Governance: We define governance as assuring the availability of and secure, authorized access to third-party data. Such governance is often made more difficult by the need to license data from multiple providers, and sometimes for each business unit to negotiate its own licensing terms.
Once the data is in-house, it is often stored in hard-to-find and inaccessible silos residing in various functional or geographic business units. The lack of a single source of truth for the data, and the need for multiple licensing agreements, raises costs, reduces agility and increases the risk of inaccurate insights through the use of inconsistent data.
Using the Snowflake Third Party Data Exchange, we integrate the third-party data for clients and create views of the data accessible for easy querying by end users, as well as templates for sample reports.
Other potential uses of our approach in the insurance space include applying third-party data originating from sources such as accident and credit reports to rank the underwriting risk of specific customers or provide targeted lists of prospects for lead generation.
In a rapidly changing world, being first to identify a problem or opportunity through the analysis of third-party data can provide a lasting competitive advantage. Yet too often, data integration and governance challenges slow the analytic process.
Used properly, cloud-based big data platforms such as Snowflake can speed third-party data integration and presentation and, more importantly, offer businesses a way to augment internal knowledge with external insights and foresights that can lead to more targeted and relevant products and services.