Data can be used to create new products and services in a variety of ways. Here are a few examples:
Identify unmet customer needs. By analyzing data on customer behavior, feedback, and industry trends, you can identify unmet needs that you can address with new products or services. For example, if you see that a lot of your customers are complaining about the lack of a certain feature on your product, you could develop a new product or service that meets that need.
Improve existing products and services. Data can also be used to improve existing products and services. For example, you could use data to identify areas where your products or services are underperforming and make changes to address those issues. You could also use data to gather feedback from customers and use that feedback to make improvements.
Create new business models. Data can also be used to create new business models. For example, you could use data to identify new ways to monetize your products or services. You could also use data to create new subscription services or other recurring revenue streams.
I recently worked on establishing a new service based on healthcare diagnostic data. In order to monetize patient's diagnostic results, there were several critical steps to consider
Analyze data market: Our marketing team provided access to market analysis tools.
Assess the data, data classification and the data ecosystem: This information will help to design the marketplace approach, monetize based on data categories and data segments, and to understand who all are involved in the current data infrastructure.
Establish a Data Access Group who'll be responsible for assessing data consumption request, pricing, impact on competitive usage and data security.
Establish a partner. Establishing a partner changed the go to market and ad-hoc resourcing dynamics for us. The partner managed all data consumption requests, which were in hundreds every month.
De-identification and Tokenization: Given that we were placing patient related data in the data marketplace, we de-identified (anonymized), tokenized the data. I'll write additional posts on this topic.
Establish data governance program to ensure data quality and data standardization. Ensure compliance with all applicable laws surrounding the publication of patient's data.
Here are some specific steps you can take to use data to create new products and services:
Gather data. The first step is to gather as much data as you can about your customers, your industry, and your competitors. This data can come from a variety of sources, such as customer surveys, focus groups, social media, and industry reports.
Analyze the data. Once you have gathered your data, you need to analyze it to identify trends and patterns. This will help you to identify unmet customer needs, opportunities to improve your existing products and services, and new business model opportunities.
Generate ideas. Once you have a good understanding of the data, you can start to generate ideas for new products and services. Be as creative as possible and don't be afraid to think outside the box.
Evaluate the ideas. Once you have a list of ideas, you need to evaluate them to see which ones are the most feasible and have the most potential. Consider factors such as market demand, competition, and your company's resources.
Develop and launch the new product or service. Once you have chosen an idea, you need to develop it into a viable product or service. This may involve creating prototypes, conducting market research, and securing funding. Once the product or service is ready, you need to launch it and promote it to your target market.
Here are some examples of companies that have used data to create new products and services:
Amazon: Amazon uses data to identify new products to sell, recommend products to customers, and improve its supply chain.
Netflix: Netflix uses data to recommend movies and TV shows to users, create new original content, and improve its streaming service.
Spotify: Spotify uses data to recommend music to users, create new playlists, and improve its music discovery features.
Uber: Uber uses data to match riders with drivers, optimize its pricing, and improve its traffic routing. Analyzed ride data to roll out new offerings like ride-sharing (UberPOOL) and food delivery (UberEATS). Their data insights allowed them to expand beyond just ride-hailing.
Airbnb: Airbnb uses data to match guests with hosts, recommend properties to guests, and improve its fraud detection systems.
Walmart: Walmart uses data to optimize its inventory levels, predict customer demand, and develop new products. For example, Walmart uses data to identify which products are trending and which products are not selling well. This information is used to stock the right products in the right stores and to develop new products that customers are likely to want.
Google: Google uses data to improve its search results, develop new products and services, and target advertising. For example, Google uses data to personalize search results for each user based on their search history and interests. Google also uses data to develop new products and services, such as Google Maps and Google Translate.
Apple: Apple uses data to improve its products and services, develop new products and services, and target marketing campaigns. For example, Apple uses data to identify which features of its products are most popular and which features are not used very often. This information is used to improve existing products and services and to develop new products that customers are likely to want.
Microsoft Azure: Microsoft Azure uses data to improve its cloud computing services and to develop new services. For example, Azure uses data to optimize the performance of its servers and to identify new services that customers are likely to want.
Spotify: Combines music streaming data with listener data to create personalized playlists and surface new artist recommendations. This data-based customization helps retain users.
General Electric: Taps into data from industrial machines and sensors to develop new services like predictive maintenance. This allows cost savings for clients and new revenue streams.
Procter & Gamble: Employs consumer panel data to come up with new products like concentrated detergents. Data revealed consumer desire for efficiency and convenience.
LinkedIn: Uses professional profile data to develop new offerings like job searching, targeted advertising, and Sales Navigator. Their data assets allowed them to expand their platform.
The key is having the data, analytics, and cross-functional process in place to turn insights into new products that align with customer needs. Companies that get this right can continuously innovate.
Sash Barige
Jan/13/2022
Photo Credit: Unsplash.com
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