Data is at the heart of meeting the elevated expectations of today's connected customers. When applied wisely, the flood of customer data from countless devices and systems of record allows companies to know precisely when, why, and how to engage at the individual level. The competitive battleground is now squarely based on superior customer experience. Companies that are data-driven will compete, grow and win. Companies that place a lower emphasis on data quality, data analysis and faster shared customer insights used to improve the customer experience, will disappear in the very near future.
Service as a product (also known as SaaP) is a business model that is globally adopted by businesses in every industry. The era of having customers purchase a product or equipment and then moving on is over. Nowadays, to ensure the customer continues to interact with your business after the product sale installation is more important than ever. The ability to provide customers with service, meet their demands and beat their expectations opens up new doors to opportunities of generating new recurring revenue streams. At the same time, it helps you stay ahead of your competition.
Your customers are supplying you with data that can help you predict the future. Now more than ever, predictive analytics are becoming available to small businesses looking to get ahead of the competition by mining their data and generating meaningful intelligence. From mapping customer purchase trends to optimizing product campaigns, predictive analytics can be the digital marketing solution your company needs.
Lack of coordination between marketing and sales is a problem which plagues many companies. It's a strange thing, given that their objectives are identical: generating and converting leads. And that's the crucial point; if there's any (professional) friction between your sales and marketing teams, the cause is usually purely operational. For example, sales and marketing might each have their own criteria for what makes a Sales Qualified Lead. In reality, they may both be right, or at least partially right, but simply coming at it from different perspectives.
Text mining predictive methods help organizations enhance the value of unstructured information by deploying insight from text analysis in software applications and business processes. Once textual information is transformed into a set of structured data using text mining (or text analytics) it can be combined with traditional data mining algorithms to generate new insight for sentiment analysis and predictive analytics. Whether it is marketing and competitive intelligence, customer relationship management, social media monitoring, operational risk mitigation or threat discovery, big data is a key element for understanding where you are and where you're going. Text mining predictive methods support organizations in staying competitive. It helps them improve the ability to quickly react to customer feedback, market changes, competitive landscape evolutions, etc.