Skip to main content

Are You Getting Better ROI without Technographics?

Technographics was around the corner since a decade, but it wasn’t discovered up till a few years back. If you break the word Techno + Graphics = you will get to see technology + data. It means study of tech stack or tech data companies or firms use for internal or external purposes, some common examples are CRM software like Salesforce, SEO tools for digital marketing, and so on. In clear words, marketing and sales companies use a lot of data to study the behavior of a particular segment they are trying to reach. For example, to android phone users you can pitch them for any App. But not to IPhone users.


To gain deeper insights about user behavior and patterns with your marketing efforts, you must be following some particular data sets perfectly aligned with demographics and firmographics. Well, that’s a little better than the traditional sources. What about today’s B2B marketing strategies. Have you ever considered understanding your customer through the analysis of their technology stack?

To help you more, here comes Technographics.

Technographics is a kind of study that will help you to understand what sort of technology a customer is using. Based on their tech stack data or records, you can curate your marketing strategies to approach them.

Technographics is Essential for B2B Marketers for the Following Purposes:
  • Segmentation
  • Preparing firmographic profiles
  • Understanding client pain points
  • Targeted marketing strategies
 Undoubtedly, technographics reinforces your business intelligence.

Comments

Popular posts from this blog

Why is Python becoming a Trend among Data Scientists?

Internet technology has set the world on fire. New revolutions are always around the corner. But did you ever notice that nowadays new revolutions are mostly based on technology and driven by data. It is data that is being generated everywhere via the internet. So what’s big deal about it? Well, the data we get from Internet is big data. Websites, social media, servers and so on...all contribute for data. It is data that is driving the demand-supply chain that serves the human race. Since we have been generating humongous amount of data every day, we have data scientists who drive value from it, so that humans can lead life of meaning and purpose and of convenient.


We now got hunch that Python has something to do with big data and work profile of data scientists. Now let’s get back to the point and seek answers as why data scientists are loving languages like Python and R over the traditional programming languages.
Let the pictures below speak for them, as a picture speaks a thousan…

What Topics in Python Should You learn for Data Analysis?

First off, understand there is difference between developing full-fledged software and doing data analysis using Python as a programming language. Clearly, here your aim is to do data analysis using Python, so learning Python becomes imperative for you. Right? Well, most of the people new to ‘big data’ and ‘data science’ go pell-mell, as they do not know where the correct essence of learning lies. They think that learning Python from A to Z will make them smarter, may be it can, but that's too much time consuming. As a new aspirant, you should be able to make out as what you should exactly learn for doing data analysis using Python.

In this post, we will go through the most-likely path which will make you self-confident in Python and subsequently in data analysis.

Step 1 - Basics:
Your learning process starts with rudimentary knowledge. Learning resources for general are different than selected learning. So, be it anything, you must learn the basics involved in Python. To learn…

What is Apache Cassandra?