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is a great tool to use for business intelligence and data analysis. If you want to eliminate manual data imports and save time, then let me will show you how you can automatically connect and import data from external sources into Google Sheets. Google Sheets The 3 best ways to import data into Google Sheets are: Google Sheets Functions Google Sheets Add-ons Google Apps Script Let's dive into each of these 3 methods in more detail. 1. Google Sheets Functions Google Sheets has 5 built-in functions that can help you import data: IMPORTDATA IMPORTFEED IMPORTHTML IMPORTRANGE IMPORTXML Let's see how we can use each of these Google Sheets functions to import external data automatically. 1a.) ImportData You can use the =IMPORTDATA function to pull data from a given URL in CSV or TSV format. Just use the function =IMPORTDATA("X") and replace X with an a URL. The URL must be enclosed in quotation marks or it can be a reference to a cell that contains the appropriate text. You can only use a max of 50 ImportData functions per Google Sheet. IMPORTDATA Syntax IMPORTDATA(url) IMPORTDATA Examples IMPORTDATA("http://www.census.gov/2019census/csv/pop_change.csv") IMPORTDATA(A1) 1b.) ImportFeed Use =ImportFeed to pull an RSS or ATOM feed. IMPORTFEED Syntax IMPORTFEED(url, [query], [headers], [num_items]) url: URL of the RSS or ATOM feed, including the protocol (e.g. http:// or https://). The url has to be in quotes or it can reference a cell that contains the appropriate text. headers: Whether to include column headers as an extra row on top of the returned value. The default is false. num_items: For queries of certain items, the number of items to return, starting with the most recent. Specifying this is optional, if num_items is not specified, then all the items that are currently published on the feed will be pulled. query: This specifies what data to fetch from url. This is optional, as the default is "items". query options: "feed" pulls a single row that contains feed information including the title, description, and the URL. "feed <type>" pulls a specific attribute of the feed, where <type> can be the title, description, author, or the URL. "items" pulls a full table of information that contains items from the feed. If num_items is not specified, then all the items that are currently published on the feed will be pulled. "items <type>" pulls an attribute of the requested item. <type> is the title, summary of the content, url, or created (the post date of the item). IMPORTFEED Examples IMPORTFEED("http://news.google.com/?output=atom") IMPORTFEED(A1,B1,C1,D1) 1c.) ImportHTML Use the =ImportHTML function to pull table or list data from a HTML page. Just use the function =ImportHTML(X) and replace "X" with a URL, query, or index. IMPORTHTML Syntax IMPORTHTML(url, query, index) url: URL of the page you want to pull information from, including the protocol (e.g. http:// or https://). The url must be enclosed in quotation marks or it can be a reference to a cell that contains the appropriate text. query: You can use either "list" or "table" depending on the type of structure that contains the data you want to pull. index: This is the index, starting with 1, that identifies the table or list as defined in the HTML source that you want to pull. IMPORTHTML Examples IMPORTHTML("http://en.wikipedia.org/wiki/Demographics_of_India","table",4) IMPORTHTML(A2,B2,C2) 1d.) ImportRange Use the =ImportRange function to pull a range of cells from a specific spreadsheet. This function requires that the sheet must have permission to import data from another spreadsheet. When you use this function for the first time, you will be prompted to enable permission. Once you give access, then any user on the destination sheet can use the IMPORTRANGE function to import data the source spreadsheet. You can revoke permission at any time. Also, if the data set you're trying to import is too big, then you'll get an error message. IMPORTRANGE Syntax IMPORTRANGE(spreadsheet_url, range_string) spreadsheet_url: This is the URL of the spreadsheet that you want to import data from. The value for spreadsheet_url must be in quotation marks or it can be a reference to a cell containing the URL of a spreadsheet. range_string: This is a string, formatted as "[sheet_name!]range", which specifies the range to pull. The sheet_name of range_string is optional. The default IMPORTRANGE will pull from the given range on the first sheet. The value of range_string must either be in quotation marks or it can be a reference to a cell that contains the appropriate text. IMPORTRANGE Examples IMPORTRANGE("https://docs.google.com/spreadsheets/d/abc123xyz456", "sheet2!A2:C11") IMPORTRANGE(A1,"B6") 1f.) ImportXML Use =ImportXML to pull data from structured data types like XML, HTML, CSV, TSV, RSS, or ATOM. IMPORTXML Syntax IMPORTXML(url, xpath_query) url: This is the URL of the webpage, which must include the protocol (e.g. http:// or https://). The value of the url must either be in quotation marks or it can be a reference to the cell that contains the appropriate text. xpath_query: This is the XPath query that will run on the structured data. You can find more information on XPath here. IMPORTXML Examples: IMPORTXML(" https://en.wikipedia.org/wiki/Apollo_11", "//a/@href") IMPORTXML(A1,B3) 2. Google Sheets Add-ons There's several Google Sheets Add-ons (aka Google Sheets apps) available in the Google Workspace Marketplace that you can use to connect different types of external data sources. A couple of the most popular Google Sheets add-ons for connecting a data source to Google Sheets are Apipheny and Supermetrics. Apipheny Apipheny.io is a Google Sheets add-on that you can use to connect any JSON or CSV API to Google Sheets. With Apipheny you can import an API to Google Sheets just by entering your API URL and headers and then clicking "Run". It's a simple no-code tool for connecting an API to Google Sheets. You can pull in API data from any JSON or CSV API data source and you can save your API request or schedule it to run on a recurring basis. It also includes features like the ability to save your API requests for easy access and the ability to schedule your API request to refresh the data in your spreadsheet on a recurring basis. There's also a custom =APIPHENY() function you can use to call an API request in your spreadsheet or you can reference the value of a cell in your API query. or and learn more. Click here to install Apipheny click here to visit the website Supermetrics Supermetrics is a reporting and marketing automation tool that you can use to pull in paid ads, SEO, social media, and other analytics data. It has a lot of pre-built data connectors ready to help you connect different data sources so you can easily pull your data into Google Sheets. 3. Google Apps Script You can use to write a simple code that will connect and import data into Google Sheets, or you can copy and paste one of the publicly shared scripts from a site like or Stack Overflow. Google Apps Script Github For example, here's how you can use Google Apps Script to import JSON data into Google Sheets: Open an existing Google Sheet or create a new Sheet Click "Tools" > "Script Editor" in the menu to open the Google Apps Script editor Delete all the placeholder content that's in the script editor so you can enter your own script Copy and paste a script from Github or Stack Overflow into the editor such as this one Choose "File" > "Save" Title the code "ImportJSON" or something similar Close the Google Apps Script editor and go back to your Google Sheets In the cell of your choice, enter =ImportJSON("X") but replace X with your JSON API URL Press enter and your JSON API data will get pulled into your Google Sheet Script vs Function vs Add-on: Which Will You Choose? Each method has it's own pros and cons. The Google Sheets functions and Google Apps Script methods are limited in functionality but they are free to use. The Google Sheets Add-ons are more feature-rich but they cost money. Depending on how simple or complex your query is will determine the right tool for your needs. Final Thoughts Importing data from various data sources into Google Sheets is easier than you might think. There's an abundance of available functions and tools you can use and there's more coming out all the time. If none of the above methods are what you're looking for, you could code your own tool using and Google Apps Script. Check out to learn how. Or you could hire someone to code it for you so you can get exactly what you're looking for. Getting a custom made solution is pretty cheap these days when you hire a freelancer from a website like Fiverr or Upwork. Google Sheets API this tutorial Related article: . how to pull JSON API data into Google Sheets

How To Import External Data Into Google Sheets Without Copy/Paste

Las 3 mejores formas de importar datos externos a Google Sheets [automáticamente]

3 ways to pull JSON data into a Google Spreadsheet In my last article, I showed you . 3 ways to import external data into Google Sheets In this article, we'll take a look at how to use a JSON API in Google Sheets and how to convert JSON data to Google Sheets. JSON is one of the and there's an abundance of resources available to help you pull into . This article serves as a summary of the available resources and a good jumping off point. most popular API formats JSON Google Sheets I've divided this guide into three sections: Code it yourself (using Google Apps Script or Python) Use a no-code tool (I cover 4 different tools) Hire a freelancer (like a data analyst or a developer) Free JSON APIs for Testing Some of the tools and recourses described below may require the use of an API URL. If you want to use a test JSON URL that doesn't require authorization, you can try one of these: : Chuck Norris Jokes API https://api.chucknorris.io/jokes/random : Pokemon API https://pokeapi.co/api/v2/pokemon/1 Click here to see a list of free public APIs you can use Okay, let's dive in... 1.) Code a JSON Importer Yourself 1a.) Use Google Apps Script The most popular method to import JSON data into Google Sheets is by using the editor and copying and pasting a publicly available from , or writing your own code. Most of the top results on Google Search for are a variation of these steps: Google Apps Script Import JSON script Github this topic Open a Google Sheet In the menu at the top of the Google Sheets, click  Tools > Script Editor In the script editor, remove all the placeholder content so you can paste your own code in Copy and paste an open source script from Github.com such as or this one this one Click the save icon (or click File > Save) Enter any name for your project such as " " ImportJSON Go back to your Google Sheet In cell A1, start typing and you'll see the function you created pop-up as an option. Click it. =IMPORTJSON Enter your JSON API URL between the parentheses in the function, between a pair of quotes. eg. =IMPORTJSON("https://cat-fact.herokuapp.com/facts") Add any other parameters you want Hit enter and your JSON API data should populate your sheet This script is completely free to use. The downside is that you're limited to what the script can do, unless you modify the code. In it's current form, the Github script is best for one-off data pulls. If you'd like something with a user interface that can automate data imports and exports, keep reading. Here's a video someone made showing the steps to use Google Apps Script: Here's a link to the script used in the video. An example of someone taking the public script and modifying it so that the data refreshes automatically can be seen here: If you're interested in automating tasks at work, and dipping your toes into coding, then is a great place to start. It has a great community around it; you can find an active Google Apps Script group on your social media of choice. And it's relatively easy to learn how to use it. by Ben Collins. Google Apps Script Here's a beginner's guide to apps script 1b.) Use Python is one of the world’s fastest and most popular programming languages used by a diverse range of professionals like data analysts, software engineers, and even accountants. Python The difference between Python and Google Apps Script is that Google Apps Script is Google's own native programming language. Some people even supplement Google Apps Script with Python. There are several reasons you might choose to use Python: Python is a multi-purpose language which makes it usable across many industries You can solve problems without writing a lot of code It’s also a multi-platform tool, which means that you can use it on Mac, Windows, or Linux The syntax is user friendly One of the most common uses for Python is creating code for a repetitive task to save you time. In this example, I'm going to show you how to use Python to import JSON data into Google Sheets. Here's the steps that you need to take (for Windows): Download the python application here: https://www.python.org/downloads/ Follow the instructions for installation (you can leave the defaults settings as-is) Once it's downloaded, you want to verify that the Python terminal was downloaded correctly. To do this, open your python application and find the version in the first line. It’s the number right after the word “Python” at the top-left corner of the window. If your interpreter matches the version you downloaded, you're verified. In your account of the software you are looking to pull API data from, find your API key and token. This is usually found in the developer section. Once you have your API key and token, move on to the next step Next you're going to install the to work with the requests in Python. Think of modules as a code template that will do part of the job for you. To do this use the command “install requests”. request library Once the request library is installed, use the command “ ” to send a request using the API URL and the command “ ”. The API URL usually consists of the domain’s API URL, you API token, and parameters that you want to pull (ex. First_Name, Last_Name, Email, etc.). import request requests.get Now you want to get the status code to see if the request was a success using the command “result.status_code”. If there is an error, use to see why your request was not successful, and adjust your code accordingly. this dictionary Lastly, you will use the command “result.json” to get the results of your API request in JSON format. Or if you would like to receive the results of your API data in text form, use the command “results.text”. And then you’re done. You've successfully pulled JSON data from an API into Google Sheets using Python. As you can see, Python is relatively easy to use, but like with any programming language, there's a learning curve. Here's a video I found on youtube of someone using Python with Google Sheets: 2.) Import JSON Using a No-Code Tool A "no-code" tool is a great option for those who want to connect and import JSON data sources in a user-friendly way. A no-code tool is just software that takes something technical like connecting data sources and presents it in an interface. Here's the 4 best no-code tools to connect a JSON API data sources to Google Sheets, in order of features and affordability: 2a.) Zapier might be the most popular tool for connecting JSON data sources between different platforms. Zapier's an automation tool for connecting different apps together. Zapier Zapier has . Check that page to see if they have an integration available for your specific data source(s). thousands of integrations available for Google Sheets The downside to using Zapier is that it won't work if they don't currently have an integration with your data source, or if their integration is limited and doesn't do what you need it to do. Unless, you want to . build your own Zapier integration as long as you only need to do 100 "tasks" per month or less. Any more tasks than 100/month and you'll need to move to a paid plan, which start at $19.99 usd/month. Cost: Zapier is free to use For example, if you’re an e-commerce store that has more than 100 orders a month, and you want to connect your Shopify orders to Google Sheets, you will need to move to a paid plan. Here's an example video someone made showing you how to connect a data source to Google Sheets using Zapier: 2b.) Apipheny Apipheny.io is an API connector for Google Sheets. Apipheny is popular with data analysts and with people who have experience working with APIs. With Apipheny, you can import JSON into Google Sheets in just a few clicks. All you have to do is open the add-on, then enter your API URL and headers/key into the add-on and then click "Run". Your JSON API data will automatically pull in your Google Sheet. You can also save and schedule your API requests so the data refreshes on a recurring basis. There's a custom function and the ability to reference the value of a cell in your API URL, headers, or POST body. All without leaving your Google Sheet. =APIPHENY() Apipheny could be right for you if you want the ability to query endpoint of an API instead of having to rely on pre-built integrations, and the ability to connect to almost any JSON or CSV data source, making it possible to connect to an unlimited number of data sources and make custom blends of data. any Apipheny is free to use with affordable paid plans. Cost: Try Apipheny free for 30 days Apipheny Website 2c.) Supermetrics is a popular marketing reporting and automation tool for PPC, SEO, social and web analytics. Supermetrics has integrations with more than 70 different platforms. It's one of the go-to choices for agencies. Supermetrics Supermetrics has a few different tools, and one of them is a Google Sheets specific add-on that you can install in the G Suite Marketplace. Using Supermetrics, you can segment different marketing channels in multiple ways in Google Sheets then use your sheets skills to make reports that really stand out. They also have a Google Data Studio connector that allows you to connect major marketing platforms directly for reporting. has a free 14-day trial and then goes to a paid plan which starts at $69 usd/month. There is a free plan but it only includes a Google Analytics integration. Cost: Supermetrics . Click here to read a Supermetrics review . Click here to visit Supermetrics' website 2d.) Funnel is an enterprise software that allows for automated data collection and marketing reports. Funnel has many integrations available - they have integrations with over 500 data sources. Funnel.io Funnel has a lot of different features, and one of those features is the ability to . So what you would do is connect your data source to the Funnel software, and then export the data to Google Sheets. export your Funnel data to Google Sheets With the Funnel software, you would be working outside of Google Sheets, like Zapier, instead of directly in Google Sheets as with Supermetrics or Apipheny. , the Funnel team shows you step-by-step how to connect your Funnel data to your Google Sheet and then schedule it as a task to refresh daily. In this tutorial and their pricing is based on your ad spend. Cost: Funnel starts at $499 usd/month If you only need a JSON connector, and want to keep costs down, then Funnel and Supermetrics may not be the right choice unless you have a need for more of their features. There's many other tools and alternatives to the tools mentioned above available depending on your needs. 3.) Hire A Freelancer The third best option to connect JSON data sources to Sheets is simply to hire a data analyst to do it for you, or a developer to create a custom solution for you. 3a.) Hire a data analyst A data analyst will either use a no-code tool such as the ones I covered in section 2 above, or they'll create a custom solution. You can hire a freelance data analyst on a website such as Upwork or Toptal. Upwork On , you can post a job for free and start getting applicants almost immediately. It's free to post a job on Upwork but making it a featured job for $29.99 helps get more applicants. Upwork I've been using Upwork for years now for a wide variety of projects and have been satisfied with the results. You have to interview and hire a freelancer yourself. It's a good option for small business owners. and then just create an account and start a job post. Choose data analyst as the category. Click here to see data analysts on Upwork Toptal is another freelancer website but it's more exclusive. Toptal puts its applicants through a difficult hiring process and they claim to only hire the top 3% of freelance talent. Toptal So if you want a true expert to help you out, Toptal might be the place to get it, but with that expertise comes a bigger price tag. (if the popup shows, you can click the "No Thanks" button at the bottom). Click here to see data analysts on Toptal Other At Apipheny we have Google Sheets experts and developers for hire. . Click here to learn more My friend and colleague, Nate Page, is a freelance data analyst who has experience working with JSON: Nate's Upwork Profile Nate's Website/Portfolio You could also look for a freelance data analyst on a website like Craigslist, Linkedin, etc. 3b.) Hire a developer If you think the scope of your project calls for a custom solution with features that other software doesn't provide, or you just want to be in control of the product, you could always hire a developer to help you out. You'll have the best luck if you specifically look for a Google Apps Script developer on a freelance site like Upwork or Fiverr. The right developer for you will depend on the scope of your project. You'll have to send your project brief/details to freelancers and interview them to see who's the best fit. . Click here to learn more about hiring a developer Final Words Importing JSON is easy with all the available resources these days. The right option for you will depend on certain factors such as the scope of your project, your technical experience (whether you can/want to do it yourself), and your budget. The most cost effective way to pull JSON into Google Sheets is to code it yourself or use a free, publicly available script, as we covered in section 1. In section 2, we covered a range of products that have been purpose built to help people connect JSON API data sources with Google Sheets. And in section 3, I gave you some resources for finding someone to help get it done for you. If you want to use a free data visualizer to present your JSON data in pretty charts, you can connect your Google Sheets to and even embed it on a website. Google Data Studio If you have any comments or questions, just let me know in the comments.

Import JSON To Google Sheets - 3 Best Ways To Do It

Las 3 mejores formas de importar JSON a Google Sheets [Guía definitiva]

There’s a lot of noise about what SEO writing is. So, let me break it to you: writing an SEO-friendly blog post isn’t about finding the perfect and unique set of keywords, throwing them on a blank page, creating content around it, and calling it a day. No, it also isn’t just about H1s and H2s. What is SEO writing then? SEO writing is about writing for both people and search engines with the goal of communicating information effectively. And as a means of bringing more traffic to your website and ranking higher in the search results. Usually with the help of on-page SEO. In this post, we’ll go through what makes an SEO-friendly blog post for both humans and search engines, in an on-page SEO approach. This blog post also includes . a free and easy on-page SEO infographic for beginners or more advanced SEO writers But before we get there, let’s start with definitions What Is On-Page SEO? On-page SEO is when you optimize the elements of a website page that are visible to the user (content, metadata, keywords, images, etc.) to better their experience. It’s called on-page SEO because visitors are able to interact with and see these elements at the front end of a website. You use on-page SEO to make your web pages relevant to search engines (like Google). So you can bring more traffic to your website as well as rank higher for your set of keywords. You could say that on-page SEO makes your content more digestible for both search engines and visitors. With that clear, let’s get into detail. 9 On-Page SEO Blog Writing Tips [+Infographic] I compiled an on-page SEO factors list that you should pay attention to if you want to write SEO-friendly blog posts, rank higher, and bring more traffic to your site. But also, an infographic for you to save and use whenever you’re . SEO writing You can skip to the end to get your free on-page SEO infographic. Or… You can keep reading and have everything completely clear at the end of this post along with the infographic. 1. Use Your Target Keyword This is the part most people obsess about. There are a lot of ways you can do keyword research, and all options can be as effective or ineffective. It depends on how well you optimize the use of these keywords. So, here’s some advice: If the keyword you’re targeting appears early on in your post, this gives Google a clue about the topic. If you throw the keyword in the middle of it instead of the beginning, it doesn’t make much sense that’s your target keyword. Use the primary keyword you’re targeting in the first 100 words of your blog post: A lot of experts say that once or twice is enough, It’s true that once or twice is enough in some cases, but if you’re writing a blog post of 3,000 words about “digital marketing” and you just mention the keyword twice, it seems pretty hard to find out the blog post is about digital marketing. Use your keyword once or twice (or more): I differ. The best approach is to not stress about how many times you use the keyword but to make sure you’re writing naturally. You can include the keyword as many times as you want as long as it sounds natural. From experience, I can tell you won’t use the keyword just once or twice. Which gets us to… Just as it sounds, avoid using the same keyword repeatedly. Avoid keyword stuffing: “ ” But you just said I could use my target keyword as much as I want Yes, as much as you want to use it, but as long as it sounds natural and not forced. Keyword stuffing was an old SEO technique in which people would stuff their keyword on a page in places where it didn’t even make sense. AVOID THAT!!! 2. Optimize Your Metadata Metadata is the information that appears on the SERP (search engine results page) to give you an idea of what the page you’re going to click on is about. The metadata elements are meta title, meta description, and URL. If you still don’t know what I’m talking about, here’s a little reminder of what is metadata and where have you seen it: And if you give it a closer look… Optimized metadata helps users have a better idea of what the webpage they’re going to click on is about. And it can help your on-page SEO as well as your engagement. Here’s my advice for this: : that, you’re not using the available space to put a catchy meta title and you’re wasting the opportunity to include target keywords. . Your meta title should have a length of between 55 and 60 characters If it’s lower than Yes, include keywords in your meta title , it’ll be cut off like in the example below. If your meta title is longer than 60 characters That doesn’t help user experience as it’s unsatisfying to people scrolling. They don’t get to see what all the title is about. To avoid this, you can use the from Moz. This tool shows you how your meta title appears on the search results of Google. So, use it! free title tag preview tool There’s something you should know about the meta description. Google usually replaces your meta description with some other section of your post, as it sees fit, to satisfy users' intent. Your meta description should have a length of between 155 and 160 characters: Putting keywords on it doesn’t directly impact SEO. The fact that you're using keywords in it and optimizing its length is just for the chance of Google choosing your meta description. That way, you can attract clicks if you write an interesting and engaging meta description of what visitors are about to read. 3. Optimize Your URL Your URL is also considered metadata, but I wanted to talk about it in a different light. So, let’s go with the basics and then some tricks for you to make your URL more effective. An URL is made up of the domain, sub-domains, and URL slug. and again, have your target keywords somewhere on those five words. Nothing too complicated. Your URL slug should have a maximum of five words But here’s where you learn something not many experts know. It's also important that there are . This is because of a website architecture principle. just two sub-domains between your domain and the URL slug It’s a bad practice that a visitor has to do more than three clicks to reach a page. This bad practice tells Google the page your URL slug represents isn’t as important. After all, it’s very far from the domain. Your page becomes relevant to search engines by being no more than three clicks away from the domain. 4. Use Headings (H1, H2s, and… H3s) Headings are a must in SEO blog writing. Aside from making your post look organized, it helps Google understand what’s the topic and how it unfolds. To write an SEO-friendly blog post, you should: According to , the keywords that you use in your H1 are the most important. And keywords that you use in your H2s are less important than your H1s, but still have an impact Include your targeted keywords on the H1 and H2s: Clicta Digital The H1 of a page is like a title/name of a book. There’s just one. Of course, you could still include another H1 on your blog post, but that would confuse search engines as to what’s the main topic Use one H1 per web page: Using H4s just looks… messy. You’ll make your visitors feel like they’re going down the rabbit hole of the internet or the topic you’re explaining. H3s is deep enough Don’t go lower than H3: Also, as a pro tip, if you format your blog post correctly for a query, it could be optimized for search intent and appear on a featured snippet like the example below. So yes, formatting is super important. The usual unfolding of SEO-friendly blog posts goes like this: H1 Main topic H2 Section break

    H3 Subtopic

    H3 Subtopic

    H3 Subtopic

H2 Another section break

H2 Conclusion If you’re a beginner in on-page SEO, you can study some of your favorite blog posts and see their structure. 5. Beware of Thin Content Thin content is content that adds no value to the user or it’s low quality. And what I mean with low-quality content is when this is: Automatically generated content from machines Higher rate of advertisements over content for visitors Low content, meaning less than 300 words on a page Or duplicate content If you want to write SEO-friendly blog posts, remember that it’s all about the visitor’s experience. And if you have already experienced finding these yourself, you know how frustrating it can be. types of thin content 6. Use Internal Links Most people don’t know the power internal links have, so they keep posting content without them. The thing is internal links are just as important as external links. Sure, external links bring traffic to your website from the corners of the internet. But how is this traffic going to flow on your website? Visitors will get to the page they wanted to read about, finish, and then leave. You don’t want that. You want to keep them engaged and make them click on another post that has a related topic. SO, . you include an internal link There’s this thing called that you have to let flow through your site. External links bring that from other pages to your website, and internal links help distribute it. Which helps Google know what posts are more relevant to your website. link juice link juice If there are a lot of internal links pointing to one of your pages, that page must be important, right? With the right internal linking strategy, you can better the SEO of your site. But you have to consider the use of anchor text. Anchor text is the underlined highlighted words that indicate an internal link. Now, here are some and to ensure the friendliness of your blog post: tips for anchor text Don’t use general words like “click here”, “read more here”, “here”, etc Don’t put the raw URL link as anchor text Don’t remove the underlined highlighted customization of the anchor text. Users won’t know if that’s an internal link because it looks like plain text, so they won’t click on it and there won’t be link juice flowing Don’t use a whole phrase as anchor text. Try to , so it doesn’t look crowded anchor five words Use keywords related to the post you’re linking back to Internal links are powerful, so . try to include a minimum of two in every SEO-friendly blog post you write 7. Optimize Your Images Search engines like Google crawl your website and analyze all the information in it to understand it and index it in the best way possible. But what happens when crawlers find an image? Well, they can’t recognize it as any other human could. And the fact that you like high-resolution images doesn’t mean Google likes them as well. They have to be optimized. Here’s how you to do it: The can affect the speed of your website and its health. If your website takes too long to load, it negatively affects your SEO. In the case of larger files, you can go as big as 100 kb Keep the file size of your image below 70 kb: image sizing and optimization Name your images: When users look at your images, they understand what are they about, but Google doesn’t. So, Google crawlers rely on the description of the image ( ) to know what is it about. or alt text Here are some tips on how to name your images: DO . And make sure the description is related to what the image shows. You can even . the image in five words or less Describe include some of your target keywords ✅” best office laptops” ✅” laptops for IT representatives” ✅” laptops with 8Gb RAM” DON’T ❌”Screenshot_20220302-32410” ❌” laptop(2)” ❌”cheap+laptop+affordable+pcs+IT+representatives+office+best+laptops” These names don’t describe your image to Google and the last one is considered keyword stuffing. So, be careful. As ridiculous as it sounds, even though you just want to an SEO-friendly blog post. The SEO part means now you have to take care of images too. write 8. Optimize for Featured Snippets A featured snippet is that piece of text that appears at the top of the search results on Google (right below the ads, of course). Some call that the . And it has the goal of showing users the information they’re looking for in the fastest and more effective way. position zero There are three steps to optimize for featured snippets: You can use tools like SEMrush to find what keywords have featured snippets and which ones are missing one. Or you can directly type on Google Make sure there’s a featured snippet spot free: : You have to use a headline with the query your audience wants solved. It’s usually an H2 Use tip #4 on this list, headlines Here you give the critical information first. Remember, featured snippets are for your audience to get what they need in the most simple and understandable way The paragraph below the headline has to immediately answer the query: “ ” But if my audience reads what they need on the featured snippet, I won’t get any visits. So, why optimize for a featured snippet? Optimizing for featured snippets is worth it. Your audience may read what they need, but if they want to understand the topic better, there’s nothing stopping them from clicking in to get more info. What’s more, even if you don’t rank #1 for your targeted keyword, featured snippets can help you pull some traffic to your website. After all, featured snippets only extracted from the #1 result. aren’t According to a study made by , almost . The fact that your page has a featured snippet makes your website the option most people would go to for more information. Supermetrics 60% of featured snippets are pulled from the search results positions between #2 and #5 9. Have Strong Readability Scores Even if the blog post you wrote has a lot of helpful information with a completely new approach and all the SEO writing tips I gave you, that won’t be enough to rank if your readers have to re-read it over and over again to understand it. That’s why having strong readability levels is important. Here’s my advice: Use a lot of periods throughout your content, it’ll make your sentences shorter and understandable Make your paragraphs short. A good rule of thumb is to have . Humans read in sections and when a section is too long, it just becomes difficult to digest paragraphs between 3 and 4 lines Don’t use difficult terms to sound smart. Simplicity is better How to make an SEO blog friendly is also about making it understandable for a wide audience. So, if you follow these tips, your readers will have a better time reading and retaining information. You can check your readability scores by using the . Your aim is to have a . The lower the score, the more readable your blog post is. . Hemingway App readability score of 9 or lower By the way, the post you’re reading right now has a readability score of 5 On-Page SEO Infographic for Blog Posts Now that we covered all the on-page elements that help you write an SEO-friendly blog post, here’s the infographic: Download your free on-page SEO infographic. You can use it as an on-page SEO guide or checklist! It’s All About the User’s Experience, Right? As you’ve already noticed, all the tips in this guide aren’t hard to follow. It’s all about presenting information in the best way possible and with the goal of helping someone solve a query. All these tips look like a lot at the beginning. But I assure you memorizing them won’t be a problem if you understand the of each and every one of them. This is why I explained it to you in every section. why I hope you found this SEO writing guide + the infographic helpful. If you have questions or observations, drop them below! Feature image by on Bulgakova Kristina iStock

How to Write SEO Friendly Blog Posts: A Complete Guide + Infographic

For many years I have been obsessing about startups and especially their management of metrics and KPIs. Just check my Medium profile and you’ll see :) It has led me to understand that knowing which KPIs to measure is not the first problem to tackle when you want to be a metrics-driven startup. The very first thing to do is to collect and access data and assure its relevance and automation. That’s the reason I moved down the data analysis value chain — so I could also help startups discover the many fantastic tools that exist out there. The goal is to achieve accessible, reliable, and automated metrics. Since I first started to explore this area two years ago, I've been hands-on helping startups to set up their data and metrics reporting. I've coached or consulted over a hundred startups, covering all industries from fintech to food tech. For you to get started, I have created multiple free templates that can help your startup at different stages, check out free resources here . If you want to be business intelligence but don’t know where to start, this guide is for you. These tools can help you easily access your data and automate your dashboards and reporting. Depending on your business model and strategies, different tools are available to you. . Most of these things you can do on your own! What I can tell you for sure is that you don’t need to hire a team of data scientists or data analysts Automated data analysis is a puzzle of different tools doing different things, and depending on your needs, skills, and business model, the tools you combine will make a system that works just right for you! ! The good news is that you don’t need to spend more than $50-$250 per month if you’re a seed-stage startup. I’ve tried SO many tools, and I’ve learned which ones are good for what I know that at first, that may sound expensive. But considering how much you’ll improve your decision-making, it’s peanuts! Let’s think of an example: If you get a better insight to your product analytics, you might be able to improve your conversion rate from download to sign-up by 20 % — if all other metrics stay equal, your revenue will then also improve by 20 %! That is probably way more than a few hundred dollars! Let’s get started! Below, you will find all the recommended tools sorted by what they do. (Full disclosure: Based on many hours of work, I have developed some favourites that I share here. Some of these favourites I've contacted to become an affiliate. There are 2 affiliate links in this article. If you think I deserve to be paid for my work, feel free to use those links :) Product Analyzers These solutions are tracking what your users are doing in the front-end of your app or website. Thanks to Product Analyzers, you can uncover your engagement metrics. This means that you can track exactly to see how your users move through your product. Find out what pages they visit, which buttons they click, and in what order. So what is really the difference between Google Analytics, Mixpanel, and Amplitude? — We have all heard of it and it is, indeed, a fantastic tool. Its biggest advantage is that it’s free. Who doesn’t love free stuff? It is super easy to get started with and therefore one of the first things that should be implemented when publishing a website. As long as your online business is only a website in the style of e-commerce or lead creation, Google Analytics is your perfect tool to track data! The most valuable information sources are funnels, and marketing attribution (where do your best visitors come from?). If you have a mobile app, I don’t recommend using Firebase with Google Analytics (unfortunately Firebase/GA for mobile apps has no API so you can’t get access to the data that you track anywhere else). What a pain! Google Analytics — This tool is the most commonly used product analytics tool. It’s available for both web and mobile apps. The most useful features include analysis of engagement, funnel, user profiles, and cohorts. This tool gives you access to all the data you need to know to improve your conversion rates and drive retention and revenue. Mixpanel “Mixpanel is the best tool for non-tech guys to get a feeling about what’s happening with their customers really fast. As soon as the events are correctly set up, it’s literally a plug and play” adds , co-founder, and CEO of , who has been using Mixpanel since the launch of his fintech app. Nicolas Reboud Shine However, it is not cheap… If you have less than 1000 monthly active users it’s for free. But once you pass that threshold, it’s a steep curve. If you have 10k users, you’ll have to . If you’re running a startup less than 3 years old with fewer than 10 employees, you are eligible for their 90 % during your 1st year. pay around $400+ per month startup discount — This tool has basically the same functionality as Mixpanel. You can segment users and create really clear funnels. The biggest difference to Mixpanel is the pricing. You can use Amplitude for up until you generate 10 million events (actions taken such as clicks or swipes). That means that you can use Amplitude for free with 10k monthly active users if they perform less than 1 000 actions per month. Amplitude also offers a , if you’ve raised less than $1M. Amplitude free startup discount of 90 % Amplitude offers an excellent API, which makes it possible to access, visualize, or analyze your data in other places than Amplitude. I’ve been helping multiple startups implementing Amplitude and I’ve had great experiences with the tool! The biggest difference between Product Analyzers such as Mixpanel and Amplitude, vs Google Analytics, is that they allow you to track individual users. You can find the logs of the different events that individual users have taken. That means that you can start segmenting and correlating different behaviours, which is very limited in Google Analytics. Other similar tools include- , . Heap Pendo The Subscription Analyzers When you are running a subscription startup, there are a lot of interesting and fundamental revenue-related metrics that can be identified using only payment data. Thanks to these tools, you can super easily get access to your Churn, Retention, MRR, etc. without knowing how to calculate these. Unfortunately, since they only rely on your data from payment platforms such as Stripe, the data stays quite shallow. These tools will tell you what your churn is, but you won’t be able to understand why. You’ll end up going in circles! If your service is a software or a digital product, I recommend you to complement these tools with some different tools to track how your users use your platform. So what is the difference between ProfitWell and Chartmogul? — This is a very popular subscription analysis tool since it’s completely free no matter your revenue! They earn their money from other services instead. Like the others, they connect with most of the common payment solutions (Stripe, Braintree, Zuora etc). ProfitWell gives you access to metrics such as Monthly Recurring Revenue, Churn, and Cohorts. Something that sets ProfitWell apart, aside from being free, is their most recently added feature. ProfitWell Earlier this year, they made it possible to insert an asynchronous JS snippet to your code. Thanks to that snippet, you can see how active your subscribers are! Pretty nifty! Unfortunately, you can’t see what actions they’ve taken, so I still advise you to complement ProfitWell with another tool to track all the engagement metrics. — Like ProfitWell, Chartmogul connects with most payment solutions. What makes ChartMogul useful for certain startups is that you can manually upload Google Sheets with the subscribers that you invoice offline. Plus, ChartMogul integrates with Google Play and the App Store, so you can also analyze mobile subscribers. Makes your life easier! Chartmogul Chartmogul is , so there is really no reason to not plug it in and start using it from the moment you onboard your first customer. If your startup is part of one of their , you can get a $50 monthly reduction! That’s like… a lot of coffee! free until reaching 10k in MRR accelerator program partners Other similar tools include: , Baremetrics MRR.io The Data Visualizers The Data Visualizers will render your excel sheet reporting obsolete. These are the tools that will allow your whole team to automate the KPI reporting and give you access to all the data that you accumulate from other tools. The Data Visualizers can be used for automated, customized dashboards and ad-hoc searches. These tools also make it easy to share data with investors or other stakeholders through email or URL links. A must-have if you ask me! If you are one of the many startups that feel like your data analysis is scattered and unstructured, this is the type of tool that you need. With these tools, you can connect the results you see in your own database and in your Product Analyzer tool with your marketing or sales activities. What is the difference between Klipfolio, Google Data Studio, and Databox? — This is an incredibly flexible tool that can get extremely powerful. It is your centralized access to all of your company’s data and metrics. Klipfolio can connect all the different tools and databases generating your company’s data. In Klipfolio you combine and treat it to make the data informative and useful. It’s your one-stop-shop! Klipfolio Connecting the data sources and Klipfolio can be a challenge depending on what tool you want to connect and the quality of the tool’s API. You connect your database to Klipfolio with a SQL query, a piece of cake for any developer to do! You can choose to use their template dashboards, but I recommend you develop your own dashboards optimized for your business and goals. Klipfolio and most of these tools have templates riddled with vanity metrics, so watch out! Klipfolio is similar to Excel to some extent, as you analyze data with the help of formulas. The biggest difference is that Klipfolio updates itself with the most recent data, so no more manual copy and paste every week. Ctrl+C? Ctrl+V? Ctrl+Bye! Moreover, it allows for automatic reports by email or Slack. Now that’s convenience. But similarly to Excel, Klipfolio takes some time getting used to and requires a learning curve. On the other hand, the customer service helps you get started… “When I needed to build my first Klip, it wasn’t as daunting as I first believed. Clicking on their support button, I got instant step-by-step human help on how to configure the Klip to display our business data,” says , Growth CMO at . Shirley Johansson Handiscover The is quite startup-friendly, starting at $49 per month for a team of 5 people. If you want a 14 days trial of Klipfolio, you can use . pricing this link — One again, Google strikes with its presence in the data analytics space by providing a free data visualizer. Unfortunately, it is very limited in use since it only automatically updates the data coming from Google products, so: Analytics, Adwords, DoubleClick, YouTube, and Sheets. Data Studio By using Google Sheets, you can manually update other data that you want to include in your dashboard, but as we know manual work is not sustainable and can quickly get time-consuming. Another alternative is subscribing to , which helps you automatically connect a few other data sources, such as Facebook, Linkedin, and Twitter. Supermetrics Another huge drawback for Data Studio in my experience is that it can’t transform your data to group them into weeks or months. So for example, if you want to group your data per month you need to hard code into your data source a new column for months. Not fun, and not quick! If you use Big Query as a database Data Studio could be of some value, but as you scale Data Studio will be very limiting. This is an easy-to-use tool which automatically helps you create interesting charts. It is very easy to set up, but also very limiting. Since everything is automatic, you have no insight into how metrics are actually calculated. This is a problem in data analysis because if a number doesn’t seem to be correct, and you don’t have any transparency in the calculation you will just lose trust in your data. Remember: it’s not just about knowing your numbers are, but also . DataBox — what why When working with this tool, I had a lot of problems with bugs. Customer service took a minimum of 24 hours up to 3 months(!) to solve these problems. On top of this, their pricing is quite expensive. For 10 dashboards (they’re really small, you fit like 4 charts into 1 dashboard) you need to . pay $119 Other similar tools include: , , , . Geckoboard Cyfe Plecto Power BI The Data Scientist’s Tools The Data Scientist’s tools are incredibly flexible and powerful if they are well installed. Data Scientists love these tools because it lets them treat large sets of data and perform advanced queries (in SQL language). The major drawback, however, is that you can’t directly connect APIs. For most of them, you can only connect data from a database. This means that if you want to summarize data in one place — from your CRM, Facebook, Google Analytics, AND your database — you’ll need to create some serious Data Management. Definitely not a good investment of your time or money if you’re running a startup. What’s the difference between Looker and Chartio? — The interface allows for both drag and drop analysis in interactive mode and a SQL mode. The interactive mode is perfect for non-technical team members to explore their data. And SQL mode allows for the more specialized team members for unlimited exploring. Chartio Compared to their competitors, they offer self-service access to their platform. This means that you can quickly get up and running for only . Not bad! If you’re a startup founded less than 2 years ago, you might be eligible for their . $400 per month 75 % discount An increasing amount of startups are asking me about Looker. It is a tool very similar to Chartio in terms of features. However, they’re better than their competitors at explaining what you can do with their tool. Unfortunately, their pricing is way out of range for what is reasonable to pay for such a tool when you’re a startup. I met a Series A startup who paid $3000 per month for Looker. Wowza! It is clear that Looker is targeting large organizations. Looker — Other tools in this category: , . Periscope Data Tableau Client Relationship Management (CRM) Tools Yes I know, this is not really a type of data analysis tool. Yet, I get a lot of questions from founders who want to know which CRMs I recommend. Therefore, I’ll include my recommendations based on my experience working with data generated by CRMs. You use a CRM to track your leads and all the interactions you have with your leads up until they convert to paying clients. The data that you generate inside your CRM is an important piece of the puzzle when you want to understand B2B customers. Here, you can learn more about what makes certain leads convert while others don’t. I recommend you connect your CRM to your Data Visualizer through their API, so you can analyze the data that your CRM generates. — It’s the oldest CRM around. It’s the original! Their focus is clearly large organizations, so it’s not ideal for startups. That said, they do offer a cheaper plan that works for startups. Unfortunately, with regard to data, I don’t recommend Salesforce. Their cheap plans don’t give you access to their API, so the data that you want to analyze is stuck inside Salesforce… Salesforce — This is a swiss knife of different tools for marketing and sales teams. Their CRM is the most valuable tool for early-stage startups. They are actively targeting startups through VCs, Incubators, and Accelerators with their . Eligible startups have 90 % off the first year, and then 25 % off. If you’re only interested in a , you can use Hubspot’s for free. Hubspot offer for startups simple CRM Free sounds really good! Unfortunately, their API is quite limited, so if you’re serious about analyzing your leads to understand how they convert, I don’t recommend Hubspot. — This tool offers a really beautiful solution for sales teams. It’s easy to set up, flexible, and very visual. The teams I’ve worked with who use Pipedrive have been really satisfied. Their pricing is very reasonable, between . for a 1-month trial. Pipedrive $12.50 — $99 per month per user Click here On top of this, ! As a data analyst, it makes me so happy to work with their API. You can achieve very powerful insights when using their custom fields, in combination with their API and a Data Visualizer. their API is absolutely magical Decisions Decisions… Whether you need tools for product analysis, subscription analysis, data management, or client relationship management, I hope this guide can help you to find what’s right for you. Well, if that's not enough, I have created multiple free templates that you can refer to for different stages of your startup, . click on the link and check out all my free resources

The Tools You Need to Master Your Startup’s Metrics

Did you know that in the next five years? And did you know that 42.3% of marketers believe that social media has a great impact on their businesses? social media spend will increase by 71% No matter what your business is, or who your customers are, adding social media to your marketing mix can take your brand to the next level. But here’s one brutal truth about social media marketing: a large number of brands are unable to effectively measure the impact of their social media marketing efforts. In fact, the claimed only 23.3% of marketers are able to prove the impact of social media marketing quantitatively. CMO survey 2018 So the question is, how do marketers measure the impact of their strategies? And is it possible to do so without spending an arm and a leg on expensive marketing tools and resources? social media marketing The answer is simple. Yes. It just takes the power of leveraging Google Analytics. In this post, we’ll cover how to effectively use Google Analytics for social media marketing to help your brand answer the most important questions around your strategy. Here’s how you can get started: Also Read: 19 Tools You Need to Know to Increase Your Organic Social Media Reach How to Set Up a Social Media Marketing Dashboard in Google Analytics With relevant quantitative data, Google Analytics easily helps you identify which social media platforms drive the maximum, targeted traffic to your site. Also, it’s possible to find out how these social media users interact with your website. In addition, setting up a Google Analytics dashboard to monitor and analyze your social media efforts helps you determine your . social media ROI Here’s how you easily set up a social media marketing dashboard in Google Analytics: Identify Your Social Media Goals & Objectives S.M.A.R.T. (Specific, Measurable, Achievable, Relevant and Timely) goals are an essential component of any successful marketing activity. Before you jump in and start tracking and measuring your social media marketing efforts using Google Analytics, you need to identify and create S.M.A.R.T. . social media goals and objectives But remember to align your social media marketing goals and objectives with your business’ broader marketing strategy. Let’s say your social media goal is to drive relevant, targeted traffic to your website. While that’s a good start, make it S.M.A.R.T. with a few tweaks: “We will increase our monthly traffic from Twitter by 20% within the next four months.” Then you’ll need to create strategies that help you achieve this objective in a timely fashion. Based on the goal above, your first step might be to use a tool like to find content in your industry that has already been highly shared on Twitter. Then create something similar on your own site and promote it on Twitter. Buzzsumo Essentially, your goals will inform your strategy as well as the metrics you track to measure success. Set Your Google Analytics Tracking Code Now that you have identified your social media goals and objectives, set up an analytics tracking code on your site. Your tracking code is what allows Google to analyze the traffic to your site so you can get quantitative, actionable data. You can use Google Tag Manager to gather tracking data. Or you can directly set up an analytics tracking code on your website. We’ll show you how to do both. How to Install Google Analytics With Google Tag Manager Using is perhaps the easiest way to collect actionable data to prove your social media marketing ROI. In fact, Google recommends using Tag Manager as it streamlines tag management on your website. This makes it easier for you to add other tags including AdWords Conversion Tracking and remarketing tags. Google Tag Manager Here’s how to add Google Analytics through Google Tag manager: Set up a Tag Manager Container code and add it on your website. Select “Tags,” then select “New,” and then select “Universal Analytics” tag type in the Google Tag Manager. Configure your tag:a. Name your Tagb. Add Google Analytics property IDc. Select Track Type according to your objectives and goals Select firing triggers. Then select “All Pages” to gather data for each page of your website. Choose “Create Tag.” Now simply publish the tag. Check out for more details on getting started with Google Tag Manager. this article from Moz How to Add Google Analytics Tracking Code Directly to Your Site Here’s how to add Google Analytics to your website: Log in to your Google Analytics account, click on “Admin.” Now select your website property from account and property columns. Now click on “Tracking Info” and then on “Tracking Code.” Simply copy the snippet. Remember, you can use only one tracking code for one website. Now paste this snippet onto each page you’re looking to monitor and track. Remember to paste the snippet before the closing </head> tag. Add Social Media Goals in Google Analytics Now that you have set up a Google Analytics tracking code for your website, it’s time to add your social media goals to your Google Analytics Dashboard. Some of the most common goals are traffic, downloads, dwell time and page views. You can add your social media goals by logging into your Google Analytics account and clicking on the “Admin” tab. Then Click on “View” and click “Goals” and “New Goal.” Let’s assume that your goal is to track total newsletter subscriptions. In that case, here’s what you need to do: Go to “Goal Setup” and add a template of your choice. However, I suggest you use the “Custom” template. Within the “Goal Description,” name your social media goal. For this case, it would be email subscriptions. In the “Goal Details” field, select the landing page or the destination for tracking and measuring your goal. Here, fill in the URL of your landing page without the domain name. That’s it. You’re done! Now save your social media goals, and it will start tracking and analyzing traffic to your selected landing page. How to Interpret Social Media Data in Google Analytics Now that you have set up a Google Analytics dashboard, it’s time to start monitoring the impact of your social media marketing efforts with the social analytics reports from Google Analytics. These reports are accessible by clicking on the “Reporting” tab, then on “Acquisition” and then “Social.” Here’s the big question: “What social analytics reports should you monitor to analyze the effectiveness of your social media marketing?” I highly recommend you integrate your Google Analytics with platforms like to simplify the process of analyzing your GA data. You can link the data with other data sources such as Facebook, Twitter and other social media platforms. Supermetrics The platform easily pulls all of the Google Analytics metrics that you need for monitoring your performance. From a single dashboard, you’ll be able to keep track of metrics such as impressions, clicks, conversions, CTR, revenue per click, etc. Here are the seven different types of social analytics reports that will help you understand how impactful your social media marketing efforts are: 1. Audience: Demographics & Interests I’m sure you’ll agree that the major objective of any social media campaign is to reach out to the right set of audiences. Remember, not every social media user is your target audience. In other words, it’s not enough to just . You’ll need to drive targeted, relevant traffic. drive traffic from social media This is where Google Analytics “Demographics and Interests” comes to your rescue. It allows you to analyze the demographic and interest information of incoming visitors to your website. This can help you understand if your are effective enough to pull the right type of audiences. social media marketing strategies In order to do this, you’ll need to filter the social media traffic from the overall traffic segment. Once you filter the traffic, this report will help you figure out if your social media targeting is effective enough to drive the desired traffic. It will provide you with insights to help you expand your audiences. 2. Audience: User Explorer Next you need to check if people are taking the desired action after they are directed from social media sites. To do so, you’ll need to analyze the journey of the user. The “User Explorer” report will help you understand what social sites are driving return visitors to your site. And how those visitors navigate through your site, and when these repeat visitors return. This report will help you understand how visitors consume and interact with your branded content throughout the buyer journey. Read Also: Top 10 SMO Tips to Boost your Website Ranking 3. Conversions This is yet another report that lets you understand the impact and effectiveness of your social media marketing strategies. Conversions could be lead form submissions, sales, email subscriptions, unique page views or sessions. With the “Conversions” report, you measure the impact of social media marketing on your conversion rate. Easily separate social media traffic as a segment to analyze conversions. But it is important to avoid taking the “last click” approach into consideration. Because social media usually drives early visits in the buyer journey, even when it isn’t the last click source leading to conversions. Looking at the data with the last click approach would not help you understand the overall impact of your social media marketing channels. Luckily, there are other means to get this information. 4. Conversions: Assisted Conversions The not-so-popular “Assisted Conversions” report gives you a complete picture of the impact of different channel sources leading to the final conversion. “Assisted Conversions” are attributed to the multiple user sessions prior to conversions. This report helps you identify the different channels that are pushing a user to enter your site before converting into an actual buying customer. 5. Conversions: Top Conversion Paths This report lets you understand the path that your users take before they convert. This means the report helps identify all of the social media sites that are driving visits to your website. It will also show you the frequency of conversions from each path. Basically, this report will help you understand how well your social media marketing is working for you in terms of pushing people down your sales funnel. Read Also: How to Improve Your Conversions with User Behavior Analytics 6. Acquisition: Social Reports This Google Analytics report focuses exclusively on social media. This report offers exhaustive insights into social traffic to help you understand the impact of the social media segment. This report offers: Overview of social traffic Overview of specific social media sites driving traffic Landing pages for social traffic Conversions attributed to particular social media sites Content engagement and user flow report These reports can offer exhaustive insights into whether the social traffic is helping you realize your goals or not. 7. Benchmarking As the name suggests, the “Benchmarking” report offers insights into your traffic and compares it against your competitors in the industry. Filter the report further to see the benchmark in different industries and segments. This report points you in the right direction and helps you improve your social media marketing strategy. Read Also: Optimize Your Site With 23 Actionable Ideas To Reduce Bounce Rate Key Takeaways It will become easier to create and optimize your social media marketing strategy if you have adequate user data in hand. And Google Analytics helps you access that data without having to run from pillar to post. Now that you know how to use Google Analytics to create, optimize, and improve your , put this knowledge into practice and get set to boost your social traffic, sales and conversions. social media marketing strategies Originally published at _S_proutSocial.com . About The Author is the Founder and CEO of (Influencer Marketing) (Content Creation) and (Graphic Design). You can connect with him on , , , and . Shane Barker Shane Barker Content Solutions Gifographics Twitter Facebook LinkedIn Instagram

How to Use Google Analytics for Social Media: A Beginner’s Guide

KPI reporting on the cheap In January this year I focussed a lot of effort on redefining KPIs for , and building dashboards to make that data transparent to the teams responsible for delivering them. kingandmcgaw.com I decided to build these dashboards in Google Sheets, using the Supermetrics plugin to automate the import of data from various sources (Google Analytics, Bing, Mailchimp, Facebook, Instagram and our back-office). Though there are many other powerful tools available, we’re already using Sheets extensively, so familiarity was an important factor. What we’ll cover Automating data collection Querying the data from summary sheets Aggregating, charting and distributing But first, examples Here is an example showing campaign KPIs: Here is another, showing trading KPIs Not exactly eye candy, but they serve their purpose well. So how do they work? Let me show you my secret weapons – Supermetrics, and the Google Sheets QUERY function. Automating data collection with Supermetrics We use to automate the collection of data from various sources. There are many subtleties to this (it probably warrants its own post), but the key is to create one sheet per data source, with date in the first column so we can query it for different time periods. Here is what our Instagram follower count looks like (I wrote about how to automate this ). Supermetrics in my previous post Instagram followers over time Using this technique, we end up with a lot of sheets within our document that are specific to each thing we’re tracking. Here is a snapshot of some of ours from the campaigns dashboard. We set Supermetrics up to import all the data each night, which means it’s always kept up to date with each full day’s activities. It would also be possible to copy/paste these values in from other sources, for a semi-manual version. Querying the data from summary sheets Once we have the raw data, we need to set up summary sheets. I’ve found that last week (LW), last month (LM) and month-to-date (MTD) fit well with our needs. Summary sheets per time period Each of these sheets has a hidden section where I hide the formulas I use to establish the date range. Here’s an example which uses various formulas to determine last month’s dates, and the equivalent period in the previous year. Hidden rows to configure date ranges and query Notice the “query” section? We can pass that into Google Sheets’ function to to pull in relevant data from our data sheets. Because the data we’re querying always has a date in column A, we’re free to pass the same query into everything on our summary sheets by referencing the cell it lives in. QUERY If you want to see a trend for the time period in question (useful to know if performance is steady or spiky), just change SUM to SPARKLINE et voila! Trendy sparklines Distributing These reports are sent weekly and monthly by email as PDFs. We use Supermetrics to do this, but you could just as easily do it with a Google Apps script, or download them and send them as PDFs. We also bring these up on a screen during relevant team meetings. Pulling it all together with an example I’ve put together an example you can view and copy. The data is randomised and the date ranges are not dynamic, but hopefully it’s enough to demonstrate some of the techniques you’ll need to make your own. . View the example dashboard In summary Collect data for each source in its own sheet, using date as the first column. Automate this if possible. Configure a summary sheet for each time period you’re interested in I hope you found this article useful. Please recommend if you enjoyed it, and add a comment if you have any questions!

Building an automated dashboard with Google Sheets (with example)

Engineering managers often rely on subjective clues to assess how their team is doing. But decisions made based on gut feel and imperfect measurements are less than ideal — sometimes they result in team success; other times they result in disappointment. Subjective measures need to be supplemented with objective data; with a combination of the two, managers are more likely to make choices that benefit their teams. When baseball managers learned this lesson, it got the Hollywood treatment. depicted the metrics-first approach to baseball management popularized by Billy Beane, then-manager of the Oakland A’s. Employing three lessons from Beane’s management approach can help engineering leaders drive productivity and efficiency on their teams. Moneyball Lesson #1: Use objective metrics Beane gained notoriety for prioritizing statistics over scouts’ instincts and consistency over flash. This approach is rooted in —  the field dedicated to “the search for objective knowledge about baseball” and statistical analysis of the sport. Though sabermetrics was founded by baseball fans, Beane applied this predilection for objectivity to managing his team. Rather than relying on scouts’ instincts, intangibles like a player’s footwork, or prestigious metrics like batting average, Beane favored a selection of under-appreciated metrics more closely correlated with consistent results. Historically, software development has been a field lacking in objective measurements. Classic workload estimates like can be useful for internal scoping but are too subjective to translate throughout an org; one team’s size “XL” project is another team’s “Medium.” Engineering leaders need objective measurements. Our version of sabermetrics involves analyzing the data generated by our own VCS, which is full of objective data about the number of Commits logged in a given period, or the length of time a Pull Request stays open before it’s picked up for review. Objective measurements can help engineering leaders measure progress across teams, projects, and quarters, and are instrumental in setting and achieving . sabermetrics T-shirt sizes effective departmental goals Lesson #2: Focus on leading indicators Of course, not all objective data is equally useful; one of the hallmarks of Beane’s strategy involved the careful selection of metrics. When recruiting, most managers looked at a player’s batting average — the number of times they hit a ball into fair territory and successfully reached first base, divided by their number of at-bats. Beane looked at their , or OBP, a measure of how often a batter reaches first base, even if they get there without actually hitting the ball. A player must be a good hitter to have a good batting average, but what puts them in a position to score a run is getting to first base. From a data-first perspective, the value of an at-bat is not in the hit itself but in the player’s two feet making it safely to first. Similarly, to the rest of the organization, your team may be defined by their most eye-catching stats and praised when they deploy a much-anticipated revenue-generating feature. But just as a player’s batting average doesn’t account for every time they get on base, a list of features completed can only reveal so much about your team’s productivity. The true measure of your team’s success will be their ability to deliver value in a predictable, reliable manner. To track that, you’ll need to look past success metrics and dig into health metrics, measurements that can help you assess your team’s progress earlier in the process. For example, an engineering manager might look at “Time to Open,” which is a measure of the period between when a developer first logs a Commit in a Pull Request and when that Pull Request is finally opened. Code can’t move through your development pipeline until a Pull Request is opened, and . Time to Open is similar to OBP. It’s not a prestigious metric, but it’s a critical one. Just as you can’t score if you don’t get on base, your team can’t deploy code that never makes it to a Pull Request. As a manager, you need to make sure that developers are opening small, frequent Pull Requests. If they’re not, it may be worth reinforcing good code hygiene practices across your team and speaking directly with developers to determine whether there’s something particular that’s tripping them up in the codebase. on-base percentage smaller Pull Requests will move through your pipeline more quickly Lesson #3: Use Metrics in Context Of course, Beane’s approach wasn’t perfect. Metrics alone can’t tell you everything you need to know about a potential player, nor do they hold all of the answers when it comes to engineering. Data is useful, but leaning too strongly on one metric is shortsighted. Though Beane was famous for seeing the value in a player’s OBP, there’s also evidence that at times, he . Not every college player with a strong OBP was cut out to play professional baseball. While a scout might be able to differentiate between a promising young athlete and one who was unlikely to succeed, a metric can’t make that distinction. As an engineering leader, you need to rely on a combination of instinct and data. Start with how you feel — is your ? — and then use metrics to confirm or challenge your assumptions. When something is surprising, consider it a signal that you need to investigate further. You might need to or find new ways to . Beane’s approach to managing his team was headline-grabbing because it was revolutionary, representing a major shift in the way fans, commentators, and managers thought about the sport of baseball. Many of his groundbreaking strategies are now commonplace, having been adopted across the league. Data-informed engineering leadership is still at that revolutionary stage. It’s not standard practice to use objective engineering metrics to assess your team’s progress or guide its strategy, but it will be. relied too heavily on that one metric engineering team moving slow re-evaluate a broken process communicate within your team

Engineering Metrics: The Moneyball Approach

To help soothe the shock of returning to work after the holidays, we've started a new tradition over at and kick off the year with a good movie or two. Since it had to be something both entertaining and inspiring, we chose to go with a classic: , the 2011 film starring Brad Pitt. Waydev Moneyball Based on true events, it tells the story of Billy Bean, General Manager for the Oakland Athletics baseball team, who started using sabermetrics, an empirical analysis of baseball that uses statistics to improve team performance. Using this new metrics-based approach, Billy Bean propelled Oakland Athletics from a low-performing team to a spectacular success that shocked the sports world. They were able to rise from what looked like a slow but certain death to a spectacular series of successes with the team winning a whopping 20 consecutive games. Here’s what we’ve learned from watching it: Moneyball Business Lesson 1: Learn to embrace change (especially when it’s the only option) The movie reminded us that change is never easy and, many times it comes as the last resort – an option that is unpopular, unwanted and fraught with dangers. The story does not portray Bean as the visionary who chose to take a new path because he’s bored with the comfort of always doing the same things. He does it because the team was sinking, and it had become clear to him that going along with the old strategy would not get them anywhere. To him, it felt like the only option. Whether you are managing a sports team, a marketing or an , there will come a time when what seems like a big change could help reach daring goals. It’s not always going to come as a last resort (hopefully!) so the ability to spot opportunities and to take risks becomes a key skill that you can and should develop. If you are lucky, you might get plenty of time and opportunities to practice before being confronted with a radical situation. So, when was the last time you took a risk with your team? – switching to a new tool, changing the way you hold meetings, or looking at your team’s performance in a different light? engineering one Moneyball Business Lesson 2: There’s magic in numbers While the movie focuses on how the Oakland Athletics’ use of statistics helped shape a winning team and triggered some revolutionary changes in the world of baseball at the time, the same often applies in business. “ ” - Peter Brand, Moneyball People are overlooked for a variety of biased reasons and perceived flaws. Age, appearance, personality. […] mathematics cuts straight through that. No manager can afford to ignore the numbers. Whether you are looking at sales reports, financial projections, or a potentially new team structure – you are most likely making business . decisions based on thorough analysis and not gut feeling While managing a team of people is far more challenging than putting together a financial report, using stats to keep track of work volumes, project progress, and each team member’s contribution can be immensely valuable. Moneyball Business Lesson 3: Others will surely follow (but probably not when you need them to) There’s a powerful moment towards the end of the movie where the owner of the Boston Red Sox baseball team, realizing that sabermetrics will be the future of the game, says to Bean “I know you've taken it in the teeth out there, but (you are) the first guy through the wall. It always gets bloody, always. It's the threat of not just the way of doing business, but in their minds, it's threatening the game. […] And every time that happens, whether it's the government or a way of doing business or whatever it is, the people are holding the reins, have their hands on the switch”. Changes are scary and feel threatening to everyone, not just to the ones making them, so expect resistance from all sides. Eventually, others will follow, but only after they see that it works and that it was the right thing to do. After witnessing the amazing results that the Oakland Athletics were able to achieve, many others followed and using sabermetrics became the norm for many teams. Only two years after Billy Bean refused Boston Red Sox’ offer to join them as the general manager for a whopping $12.5 million salary, the Red Sox won the World Series using the strategy that he helped model. There’s clearly a lesson in that, but we’ll let you ponder what it could be. If you what to start tracking the output of your engineering team , you can do it now with tools like Gitprime , Code Climate or Waydev . The article was published first on Waydev Git Analytics Blog

3 Business Lessons We (Re)Learned (Re)Watching Moneyball at Waydev

As hot as stories about artificial intelligence (AI), augmented/virtual reality (AR/VR), blockchain , and the Internet of Things (IoT) have been in recent months, we often can’t help but think of these technologies as a long way off from mainstream adoption. Movies like Ready Player One and Avengers: Infinity Wars only perpetuate this perception by mixing real technologies with fantasy, making the tech we wield in the real world seem primitive in the process. The reality, though? AI, AR/VR, blockchain, and IoT are already playing an important role in our everyday lives, with countless examples hiding in plain sight. In Part One of our series, we look at Artificial Intelligence (AI) . Artificial Intelligence is NOT Killer Robots In pop culture, AI is often represented as a highly-evolved and self-aware artificial “brain” in a robot capable of overthrowing the human race, as in or . Ex Machina The Terminator movies In reality, AI is overwhelmingly beneficial to humans and is more often associated with software applications than with robots. And it’s already here, in applications we use every day. Mapping and Ridesharing Google Maps being able to predict your commute time or suggest the fastest possible way to work relies on , a form of AI which leverages the vastness of historical trip data to make predictions or decisions. So too does Uber or Uber Eats, when it tells you the estimated time it will take for your chow mein to arrive. machine learning (ML) What’s perhaps even more impressive is that Google is able to , and then use ML to keep Google Maps updated. use computer vision (CV), another form of artificial intelligence, to “read” street signs in images captured by its Street View cars Google Maps analyzes historical trip data to let you know how to go somewhere and how long it might take. Ecommerce and Customer Service By now, you’re probably aware that Amazon analyzes your shopping behavior on its website and shows you merchandise you’re the most likely to buy, based on past page browsing and purchase history. That’s ML/AI, too. So too is the Seattle tech giant’s Alexa, an AI assistant that can do everything from control your home appliances to help you order another box of diapers from Amazon. (How convenient!) It’s not just Amazon that’s investing heavily in AI assistants; Microsoft, Google, and Apple are a few others who have introduced such AI personalities to the world as Cortana, Google Assistant, and Siri, respectively. Machine learning algorithms are also being used to automate warehouse operations, allowing companies like Amazon to fulfill upon their lightning fast delivery expectations. Businesses that must provide customer service or support are now turning to AI-enabled chatbots, which are capable of interacting with customers without human input. These chatbots allow businesses to provide a level of service that most customers find acceptable for routine inquiries, without having to employ a large workforce of customer service reps. Dating & Social Networking The dating apps you (or your single friends) use are investing heavily into AI/machine-learning to provide even better matches for you to swipe left or right on. Tinder, for example, which uses AI-based matching to occasionally suggest four users it thinks you have a great chance to hit it off with, offering you a free “Super Like” to use on one of the four. (Using a “Super Like” increases a user’s likelihood of matching by three times, according to Tinder.) began testing a new feature last year called “Super Likeable,” Another ML feature in Tinder is the ability to have Tinder automatically use your best, most successful photos in an automated form of A/B testing. This is something a competing service, OKCupid, has implemented as well. When OKCupid users are not using their most effective photos, the app alerts them so they can change to a better photo. Dating apps (or even social networking apps, for that matter) that gain a mastery over machine learning algorithms will absolutely turn the industry on its head — imagine not having to swipe at all to meet your perfect match after your first month, because the app has learned exactly what you’re looking for. Tinder’s Super Likeable feature occasionally present you with four matches Tinder’s AI algorithms thinks are especially great for you. Advanced Analytics in Sports Are you a fan of the NBA? Computer vision (CV) and AI are becoming an important tool in every NBA team’s arsenal. Back in 2013, a company called SportsVu partnered with the NBA to provide six motion capture cameras in every NBA arena. The cameras generated data that was then able to be used to provide all kinds of machine learning-based observations that quickly proved superior to mere human observations. Today, a company called Second Spectrum has the rights to provide this rich motion capture data to every NBA team, and its services are a big reason why teams like the Golden State Warriors are all-in on “small ball” and three pointers. Major League Baseball (MLB) has been using artificial intelligence even longer than the NBA, as anyone who’s watched Moneyball probably knows. MLB teams use , or advanced in-game statistical data, to model game outcomes when using different lineups (such as pitchers), batting orders, or other tactics at a manager’s disposal. sabermetrics Music Recommendations Going back to consumer applications, if you’ve ever used Spotify’s , you’ve allowed (perhaps unwittingly) an AI to dictate your musical preferences. (Don’t feel bad, though; pretty soon, AI will tell us what to wear, eat, and do with our lives — and we’ll gladly listen!) “Discover Weekly” feature Spotify’s “Discover Weekly” uses machine learning to give you curated playlists of songs you “should” like. Avoiding Killer Robots Any responsible overview of artificial intelligence should introduce the idea of , the theoretical point at which super AI becomes capable of rapid self-improvement, such that it would no longer need humans and therefore could theoretically pursue our extinction. technological singularity So real is this possibility to some that Elon Musk, CEO of Tesla, has gone on the record to say: “With artificial intelligence, we are summoning the demon. You know all those stories where there’s the guy with the pentagram and the holy water and he’s like, yeah, he’s sure he can control the demon? Doesn’t work out.” However, most experts agree that this is a scenario we won’t need to worry about with proper governance and is not even likely to be in the cards until 2040–2050 at the earliest. (There’s no need to lock up your Roomba just yet.) Today and for the foreseeable future, AI is benign, pro-human, and is proving enormously valuable for companies that choose to implement it into their applications. “With regard to mobile apps, AI is one area in which we’re seeing massive interest. AI-enabled mobile apps are particularly interesting because anybody with a smartphone — even a 5 year old phone — running a well-developed app can tap into the wisdom of billions or trillions of data points from users who came before. That’s the beauty of cloud computing and AI,” explains Harry Lee, CEO of , a in Los Angeles and the San Francisco Bay Area. CitrusBits leading mobile app development agency In Part Two of our series, we’ll explore how Augmented Reality and Virtual Reality (AR/VR) are quickly becoming a modern reality and discuss some of the most interesting applications today.

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