Consumer product warranties: 3 ways big data can optimize value
News of poor service reaches more than twice as many people as praise for a good experience, according to the White House Office of Consumer Affairs in a Better Business Bureau report. That's why CPG brands need to see their sales through for years to come. With consumer product warranties, companies can back the value of the goods they sell. Shoppers, knowing that their purchases are covered, can rest assured that they're safe from investments gone wrong.
The challenge, however, is optimization. It's impossible for brands to know ahead of time whether or not a product will fail and generate unforeseen costs. Not to mention, consumers may not be aware of the warranties that come with their purchases. Here are three ways big data can help.
1. Synthesize field product performance
Sheila Brennan, a program manager for IDC Manufacturing Insights, explains that by "synthesizing field product performance, service and customer data from multiple sources," companies will be able to detect potential problems earlier, optimize spare-parts planning and improve forecasting accuracy.
CPG leaders can reinvest this knowledge into product enhancements. When flaws are caught early enough, companies can make faster incremental changes to their product pipelines. Field product performance in the moment expedites information transmission through a big-data feedback loop.
Over time, this process will become faster and more efficient. The key is to use consumer product warranties as mechanisms to listen and learn.
2. Optimize price and duration
A paper in the Journal of High Technology Management points out that warranties fulfill two marketing needs. First, they offer promotional value in attesting to a product's reliability. Second, they provide assurance to consumers who may experience post-purchase remorse.
There is, however, a tipping point where warranties stop being cost effective, and where expenses outweigh sales revenue. Determining an ideal time limit and coverage scope can feel like a game of darts in the dark. Over time, though, companies improve their precision.
Big data improves the prediction process. According the Journal of High Technology Management paper, by evaluating multiple variables such as optimal price and warranty length, analysts can estimate the overall maximum profit for a particular product. From there, organizations can build models to optimize warranty price points and durations.
3. Understand consumer lifetime value
Consumer lifetime value is one of the most important metrics that CPG leaders can improve. From a quantitative perspective, this number represents the collective outcome of all brand loyalty, marketing and buyer satisfaction initiatives. To optimize consumer experience and aggregate value, CPG leaders need to concentrate on each shopper individually. That's where big data comes in.
As Warranty Week points out, companies can use big data to connect the dots between warranties, consumer growth and retention. CPG leaders and warranty providers can position their fragmented, transitional data points into a comprehensive consumer relationship story. This data offers more than just a product-centric view.
Big data's applications in consumer product warranties are limitless. Organizations can start by identifying historical pain points to highlight suspected areas of failure. The next step, through big data analytics, is to speed up the analysis process through new machine learning models and tools.
Over time, organizations will have a consistent system and feedback loop within their production cycles and warranty-pricing strategies. The key for CPG leaders is to listen, learn and evaluate big data within the context of their marketing and product roadmaps.
Arm your business with analytics to predict the success of your product line. Connect with data professionals via the IBM Consumer Products solutions page.