{"id":3407,"date":"2019-12-04T11:06:14","date_gmt":"2019-12-04T11:06:14","guid":{"rendered":"https:\/\/www.revuze.it\/?p=3407"},"modified":"2019-12-04T11:06:14","modified_gmt":"2019-12-04T11:06:14","slug":"unstructured-data","status":"publish","type":"post","link":"https:\/\/www.revuze.it\/blog\/unstructured-data\/","title":{"rendered":"Why Unstructured Data is the new BFF of Product Marketing"},"content":{"rendered":"\n
Understanding unstructured data is becoming more and more critical, as due to several different drivers, unstructured customer opinions and feedback is growing at a scary pace. In fact per IDG it is growing at a rate of 62% per year and IDG predicts that by 2022, 93% of all data will be unstructured<\/a>. <\/p>\n\n\n\n With so much data out there from customers, how can anyone afford to ignore it?<\/p>\n\n\n\n You\u2019d expect it to be well defined but Product Marketing is actually somewhat fluid and varies between organizations. Just try Google-ing Product Marketing and you\u2019ll see. What makes it so difficult is that it bridges multiple domains – product, marketing as well as sales. <\/p>\n\n\n\n At its core it\u2019s all about knowing the target customer and learning more about them to improve sales, product and marketing efficiency for these customers. <\/p>\n\n\n\n It typically includes activities such as:<\/p>\n\n\n\n With so many customer feedback channels and the growth of unstructured data, there is a huge opportunity today for brands to understand their customers and markets at scale and respond quickly to issues. Just a few years back understanding markets was heavily relying on manual research that was slow and not always wide enough, and brands used to take months if not years to recover from mistakes. A failed product launch could literally continue to fail for 6 months till the brand figured just parts of it out and started to correct course.<\/p>\n\n\n\n These days there is no shortage of data, but it\u2019s more complex \u2013 it\u2019s unstructured data. Unstructured means there is no specific pattern to the data. Examples of structured data could be an address, name or credit card numbers that have a well-known pattern and are easy to be recognized by technology. <\/p>\n\n\n\n Unstructured data examples are calls into the service center, online reviews, social media mentions and open-ended survey questions. None of these have a well-defined structure. Each can be of variable length, around different topics etc.<\/p>\n\n\n\n There\u2019s a huge opportunity to mine this data to gain deep insights into the things that are top of mind to your customers.<\/p>\n\n\n\n There are several types of solutions that mine unstructured data. The ones that are more detailed in nature are called Voice of the Customer (VOC) or Customer Experience (CX) analytics. For a deeper perspective on what makes such solutions more actionable, see a recent post titled \u201cThe 3 capabilities of an actionable CX analytics solution<\/a>\u201d.<\/p>\n\n\n\n As you can see there is a lot of valuable information in unstructured data. Another key benefit here is that these insights are delivered by technology in speeds that were not available before. When you connect the type of insights to the speed of insights, a product marketer can gain from VOC and CX analytics systems:<\/p>\n\n\n\n Considering the product marketer typical activities, you can easily draw the line between the above insights and successful market research, product content and sales tools, product launch lifecycle and industry engagement.<\/p>\n\n\n\nUnstructured Data<\/h2>\n\n\n\n
What is Product Marketing?<\/strong><\/h2>\n\n\n\n
What you can find in Unstructured Data<\/strong><\/h2>\n\n\n\n
Typically, you can expect to find these insights in unstructured data:<\/h3>\n\n\n\n
Benefits for Product Marketers<\/strong><\/h3>\n\n\n\n