For those who want to speak fluent ‘data-ese’, knowing the basic terms is something you cannot do without. Here are a few words to add to your lexicon this week.
Data-as-a-Service (DaaS): It is a highly customized marketing asset that is made up of Hard-to-Find-Data (HTFD) and unique data that provide an unbroken stream of qualified leads. These leads are picked up by their digital footprints and in real-time, you can offer them your products depending on their online behavior; even if they are not particularly looking to buy something online.
Siloed Data: A data silo is a dumpyard for data. Though it may sound crude, most companies have separate data silos for different departments which are not integrated which each other, which renders the data dead. For example, one department may use the contact details to target a customer, while not knowing their purchase history. It might lead to the customer feeling unappreciated, and eventually the loss of a lead. Integrated silos make the data come alive, and reduce chances of disconnected behavior that may impact the organization.
Fast Data: When Big Data is continually processed to reveal insights in real time, you get fast data to act swiftly. It is different from Daas in the sense that as the latter gives you leads in real time, the former gives you the opinions, events, and choices that are popular in the present moment. As customers look up for your products or your competitors’, make transactions, book flights, post statuses, or tweet hashtags, you know where the action is required – which gives you an incredible competitive edge. It is important for targeting in-market users and businesses to up your ROI.
Dirty Data: In 2014, Ascend2 did a survey which revealed that almost 36% marketers believed dirty data – or data which is inaccurate or outdated – is the major cause of failed marketing automation. Data decays at the rate of 2%, which might not seem much to you unless you translate it numerically: in every 30 minutes, 75 phone numbers and 120 business addresses change; 30 CEOs change jobs; and 30 new businesses crop up. No wonder then that dirty data is the major reason for CRM failure. Wrong data means losing out on customers: either by not being able to contact them due to wrong communication information or by losing their trust by presenting them incorrect data.
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