Best Twitter Analytics Tips for Your Business

Written by: admin Date of published: . Posted in test

Twitter, with its wide reach and demographics, is an important tool in expanding your business’ social media presence. This article provides actionable tips for Twitter analytics that will help you decode information and provide insights into the engagements on your posts. Twitter analytics empowers you to understand your followers and evaluate your Tweets so you can create posts that resonate with your audience.

Twitter is a mine of information and people love it because it plugs them into all the latest news, events, and trending topics. These statistics are proof- 

Tips To Use Twitter Analytics

Achieving the maximum impressions and engagements requires insights that are only available through data analysis. Here are a few tips to use Twitter analytics to extract information from your data.

Gain insights into your audience: The followers tab in the Analytics Dashboard gives you a lot of data about your followers’ interests, location and demographics. It provides information about the other people your followers follow, their top five interests, etc. When you have credible data about your followers, you can create and post content that is aligned with their interests and lifestyle. The analytics also allows you to compare your followers to other categories and gives you information about the growth of your follower base.

Understand what tweets work for you: It is essential to understand the type of content your followers like in order to improve your engagements. Engagements are actions that people take once they are exposed to your Tweets – follow, retweet, like, click on a link etc. Engagement rate is the number of total engagements divided by the total number of impressions for a tweet. Analytics helps you to keep a tab on your post impressions and engagement. They calculate the engagement rate of each tweet, present the data as a comprehensive table which gives an overview of each one of your Tweets. Following the metrics will give you a clear idea of which posts were liked and which weren’t while providing a guideline for future content.

Know when to tweet: The Tweet Activity tab gives you an overview of the metrics of your posts. You can view the entire engagement and performance history of a post over a set period of time or since it was created. Analytics help you to see the bigger picture by generating data. You can generate it in two ways – based on a date range which analyzes the impact of all your tweets within that range or based on a specific tweet. Close examination of the data will give you a fair idea of what to post and when to post.

Leverage events: The events tag on the Twitter Analytics dashboard gives you a heads up on all upcoming events, holidays and recurring trends. It gives you a very clear picture of what is being Tweeted and the trending hashtags. It has different tabs which list out all the events for a particular date. These can then be sorted for greater clarity, according to event types and location. You can leverage this information to create content that is relevant to the trending events.

Track the performance of your ads: Twitter analytics provides you with a chart that gives you an overview of your paid Tweets’ performance. In the Tweets tab, there is an option for Promoted Tweets where you can get all the data about impressions and engagements for all your Twitter Ads. It also allows data comparison and gives Conversions information. It creates a comprehensive picture of your Twitter ads campaigns and their performance. The ads data is only available for 91 days, hence it is useful to download the data regularly and save it. 

Check the growth of your followers: Twitter analytics can generate an interactive timeline that gives you insights into your followers and their interaction with your tweets. It provides information about the exact follow count of any given day. The timeline can be traced back to the day the account was created. Follower statistics can give insights into your interaction with your audience and help to streamline the activities on your Twitter account and accelerate follower growth rate.

Capitalize on your successes: The Analytics give a comprehensive view of all posts and their performance. The tweets that perform well are the ones where everything such as – tone, language, hashtags, day and time of the post was done right. Take a combination of your top performing tweets and study them to get a good idea of what worked. Use these results to create a content strategy for your brand.

Key Account Metrics To Track

There are three important metrics that you need to pay attention to as they provide a summary of your account activity. These metrics are:

Top followers: These are people who follow you and have the greatest number of people following them. They can expand the visibility of your posts through retweets and favorites. Also, top followers are either influencers or are connected to influencers and this can help you if and when you need to recruit one.

New followers: New followers are people who have been exposed to your content, have received some value from it, and decided they want to see more of the same from you. If your follower base is growing, your content strategy is working.

Top tweet: The tweet that has the maximum impressions for a given period of time is your top tweet. Its success at reaching more people speaks of the efficiency of your content strategy and all that you are doing right.

Key Ad Metrics To Track

While impressions and engagements are important metrics to track, you cannot ignore other key metrics that define your Twitter ads strategy. These include:

Results: Each ad is aligned to a desired action that you want your followers to take. Twitter ads results can assist in tracking a number of actions which include impressions, engagements, views, link clicks and conversions. These metrics will help to determine whether your ad strategy is delivering on its promise or not.

Cost per result: It is essential to know how much you are paying for each user action. These include actions such as retweets, likes, link clicks as well as impressions. Tracking the CPR will help you keep on top of your budget and also provide you with an insight into the ROI.

Wrapping Up…

Hopefully, these tips to use Twitter Analytics will help you understand the performance of your Twitter posts better and help you create and promote Tweets 

that have a better engagement rate. It will also help you to plan your Twitter ads campaigns, so they are more efficient and deliver you the best CPR and ROI. 


avatar

Koushik Marka is the founder and CEO of Studiotale, an explainer video production company. He is passionate about helping brands grow with video and has expertise in video marketing, 2D animation and Vector Illustration. When he is not working, he loves playing video games and travelling.

The post Best Twitter Analytics Tips for Your Business appeared first on SiteProNews.

Best Twitter Analytics Tips for Your Business

Written by: admin Date of published: . Posted in test

Twitter, with its wide reach and demographics, is an important tool in expanding your business’ social media presence. This article provides actionable tips for Twitter analytics that will help you decode information and provide insights into the engagements on your posts. Twitter analytics empowers you to understand your followers and evaluate your Tweets so you can create posts that resonate with your audience.

Twitter is a mine of information and people love it because it plugs them into all the latest news, events, and trending topics. These statistics are proof- 

Tips To Use Twitter Analytics

Achieving the maximum impressions and engagements requires insights that are only available through data analysis. Here are a few tips to use Twitter analytics to extract information from your data.

Gain insights into your audience: The followers tab in the Analytics Dashboard gives you a lot of data about your followers’ interests, location and demographics. It provides information about the other people your followers follow, their top five interests, etc. When you have credible data about your followers, you can create and post content that is aligned with their interests and lifestyle. The analytics also allows you to compare your followers to other categories and gives you information about the growth of your follower base.

Understand what tweets work for you: It is essential to understand the type of content your followers like in order to improve your engagements. Engagements are actions that people take once they are exposed to your Tweets – follow, retweet, like, click on a link etc. Engagement rate is the number of total engagements divided by the total number of impressions for a tweet. Analytics helps you to keep a tab on your post impressions and engagement. They calculate the engagement rate of each tweet, present the data as a comprehensive table which gives an overview of each one of your Tweets. Following the metrics will give you a clear idea of which posts were liked and which weren’t while providing a guideline for future content.

Know when to tweet: The Tweet Activity tab gives you an overview of the metrics of your posts. You can view the entire engagement and performance history of a post over a set period of time or since it was created. Analytics help you to see the bigger picture by generating data. You can generate it in two ways – based on a date range which analyzes the impact of all your tweets within that range or based on a specific tweet. Close examination of the data will give you a fair idea of what to post and when to post.

Leverage events: The events tag on the Twitter Analytics dashboard gives you a heads up on all upcoming events, holidays and recurring trends. It gives you a very clear picture of what is being Tweeted and the trending hashtags. It has different tabs which list out all the events for a particular date. These can then be sorted for greater clarity, according to event types and location. You can leverage this information to create content that is relevant to the trending events.

Track the performance of your ads: Twitter analytics provides you with a chart that gives you an overview of your paid Tweets’ performance. In the Tweets tab, there is an option for Promoted Tweets where you can get all the data about impressions and engagements for all your Twitter Ads. It also allows data comparison and gives Conversions information. It creates a comprehensive picture of your Twitter ads campaigns and their performance. The ads data is only available for 91 days, hence it is useful to download the data regularly and save it. 

Check the growth of your followers: Twitter analytics can generate an interactive timeline that gives you insights into your followers and their interaction with your tweets. It provides information about the exact follow count of any given day. The timeline can be traced back to the day the account was created. Follower statistics can give insights into your interaction with your audience and help to streamline the activities on your Twitter account and accelerate follower growth rate.

Capitalize on your successes: The Analytics give a comprehensive view of all posts and their performance. The tweets that perform well are the ones where everything such as – tone, language, hashtags, day and time of the post was done right. Take a combination of your top performing tweets and study them to get a good idea of what worked. Use these results to create a content strategy for your brand.

Key Account Metrics To Track

There are three important metrics that you need to pay attention to as they provide a summary of your account activity. These metrics are:

Top followers: These are people who follow you and have the greatest number of people following them. They can expand the visibility of your posts through retweets and favorites. Also, top followers are either influencers or are connected to influencers and this can help you if and when you need to recruit one.

New followers: New followers are people who have been exposed to your content, have received some value from it, and decided they want to see more of the same from you. If your follower base is growing, your content strategy is working.

Top tweet: The tweet that has the maximum impressions for a given period of time is your top tweet. Its success at reaching more people speaks of the efficiency of your content strategy and all that you are doing right.

Key Ad Metrics To Track

While impressions and engagements are important metrics to track, you cannot ignore other key metrics that define your Twitter ads strategy. These include:

Results: Each ad is aligned to a desired action that you want your followers to take. Twitter ads results can assist in tracking a number of actions which include impressions, engagements, views, link clicks and conversions. These metrics will help to determine whether your ad strategy is delivering on its promise or not.

Cost per result: It is essential to know how much you are paying for each user action. These include actions such as retweets, likes, link clicks as well as impressions. Tracking the CPR will help you keep on top of your budget and also provide you with an insight into the ROI.

Wrapping Up…

Hopefully, these tips to use Twitter Analytics will help you understand the performance of your Twitter posts better and help you create and promote Tweets 

that have a better engagement rate. It will also help you to plan your Twitter ads campaigns, so they are more efficient and deliver you the best CPR and ROI. 


avatar

Koushik Marka is the founder and CEO of Studiotale, an explainer video production company. He is passionate about helping brands grow with video and has expertise in video marketing, 2D animation and Vector Illustration. When he is not working, he loves playing video games and travelling.

The post Best Twitter Analytics Tips for Your Business appeared first on SiteProNews.

How to Get Your Social Media Followers to Do Your Video Marketing for You

Written by: admin Date of published: . Posted in test

In 2019, at least 80% of time spent online will involve either watching or sharing a video. Eighty percent. Put another way, eight out of every ten people you see on the subway, in the gym, or waiting for a table at a restaurant on their phones could be in the midst of consuming video content.

That isn’t exposure you want to miss out on.

According to Forbes, 90% of people claim video can help them make a buying decision. Often, seeing products in action on a website can help convince a person to make that conversion and become a customer.

Of course, exposure isn’t that simple, and we encourage you to take a look at the bigger picture when it comes to online video. Five hundred million people watch videos on Facebook every day. 

In fact, the social media giant is becoming a hub for native content that outpaces even YouTube.

Let’s face facts – unless you’re Amazon, your website likely isn’t getting that kind of exposure.

Let’s think about why, for a moment; as stated right here in one of our infographics, Facebook remains the largest social media network on the planet, with just over 2 billion users. 

Obviously, those users are going to consume a large share of video content – but it’s more than sheer numbers.

Why Social Media Video Is So Effective

If you’re scrolling through Facebook on a mobile device, like most users are these days, any native video you come across begins playing the moment it enters your screen and continues until the moment it exits a few seconds later. That means, there’s motion on your screen – whatever the content is has a little time to catch your eye before you’re on to the next thing.

If it does a good enough job of catching your eye, you’ll pause and watch some – or all – of the video. If it’s an ad, the hope is you’ll stick around long enough to view the message, the branding, and maybe even click through to the company’s Facebook page. For argument’s sake, let’s say the ad is for a product you feel you could use, so you click through.

Once you’re there, you can see what the business has to offer. They can expose you to the full sales pitch, link you to their homepage, even offer you a way to purchase on Facebook if you want – and they got you there by using video.

You knew all that before, though – it’s why you’re here, trying to determine how you can get others to do your social media video sharing for you. So let’s rewind a bit, back to the moment where the video you were scrolling past caught your eye.

It’s an ad again, but this time, what catches your eye is the video on its own merits, rather than the product it’s selling. You continue watching because whatever it is resonates with you somehow – maybe it’s funny, or touching, or thought-provoking. Maybe it’s just interesting. The point is, you’re into the video before you even see the product or service it’s trying to sell you.

So into it, in fact, you want friends to see it and laugh, cry, or think deep thoughts just like you did. You tag a few friends on the video thread itself, and they go watch the video; maybe a few friends notice the activity in their news feed and watch it too.

Or (better yet, if you’re the business who sponsored it) you share it on your Facebook page or to a group and all 1,374 of your friends have a chance to see it and discuss.

The business, obviously, hopes this activity continues, bringing more exposure for their product or service, more click-throughs to their social media page or website, and more customer conversions from an ad they only had to pay Facebook once to promote – all your shares, likes, and tags were free, in a sense.

Got It. Now, How Do I Do It?

We’ve established that video content on Facebook (we’ll save Twitter, Instagram, Snapchat and YouTube for another day) gets a lot of exposure. With autoplay, even the most boring videos garner at least a few milliseconds worth of a view, but how do you get people to watch your video long enough to get to your brand, your sales pitch, or your call to action? One word:

Entertainment

Facebook has become a news source for many people, but primarily, its roots are in entertainment. When people scroll down their news feeds, they’re more likely to stop on content that interests them. Since most users access Facebook for entertainment purposes, video that’s intriguing in and of itself is more likely to be watched to completion and shared with others.

Users who like a product may still share a video of a product they like – but only if the product is some new, fascinating innovation they feel friends should take a look at. 

If your company sells soap, for example, there’s not a lot of room for soap innovations that shock and wow the public, so you’re better off producing a video that’s interesting on its own merits.

Dr. Squatch, a soap company based in San Diego, did just that. Company founder Jack Haldrup had found an unconventional target market for his naturally made soaps – Midwestern men who wanted to use a natural soap that wouldn’t irritate their skin; unusual, in this case, because that’s the demographic that tends to think natural products are for hippies (to paraphrase Haldrup’s own words).

However, Haldrup knew that this demographic could mean a dramatic boost in sales if only he could draw them in. The problem was that he doubted most were the type to enter “natural men’s soap” into a search bar.

The solution? 

Facebook ads. Specifically, a hilarious Facebook ad that’s been viewed over 12 million times and grew his subscriptions by over 60%, primarily from users running across the ad, having a chuckle, and passing it along to their friends.

Consider companies such as Squatty Potty, with its rainbow-pooping unicorn or Dollar Shave Club, drawing its male base in with a few, well-timed drops of the f-bomb. Those videos were shared far and wide because they made people laugh – they provided entertainment.

So, What about My Company?

Perhaps your company’s brand doesn’t mesh well with humor – crude or otherwise. Consider producing a video that tugs at the heartstrings or features an adorable child saying something precocious you know every mom can relate to – a video worth watching, and sharing, in its own right.

These are the types of video ads you can count on your customer base to share among themselves.

Keep in mind that many users elect to turn off the autoplay feature, so make sure your video graphics are appealing without sound – and entice the user to tap that volume button. And while we’ve been harping on about entertaining videos, make sure you include a clear, visual, call to action so all your new viewers can click through to see what you’re all about.

Make 2019 the year your video ad is the one everyone’s talking about, and sharing with their friends – just remember to make your video worth the watch in its own right, and get your customers to do a little of your social media marketing legwork for you.


avatar

Stephen Moyers is an out of the heart writer voicing out his take on various topics of social media, web design, mobile apps, digital marketing, entrepreneurship, startups and much more in the cutting edge digital world. He is associated with SPINX Digital a Los Angeles web design company & digital marketing agency. When he is not writing, he can be found traveling outdoors with his camera. You can follow Stephen on Twitter @StephenMoyers

The post How to Get Your Social Media Followers to Do Your Video Marketing for You appeared first on SiteProNews.

How to Get Your Social Media Followers to Do Your Video Marketing for You

Written by: admin Date of published: . Posted in test

In 2019, at least 80% of time spent online will involve either watching or sharing a video. Eighty percent. Put another way, eight out of every ten people you see on the subway, in the gym, or waiting for a table at a restaurant on their phones could be in the midst of consuming video content.

That isn’t exposure you want to miss out on.

According to Forbes, 90% of people claim video can help them make a buying decision. Often, seeing products in action on a website can help convince a person to make that conversion and become a customer.

Of course, exposure isn’t that simple, and we encourage you to take a look at the bigger picture when it comes to online video. Five hundred million people watch videos on Facebook every day. 

In fact, the social media giant is becoming a hub for native content that outpaces even YouTube.

Let’s face facts – unless you’re Amazon, your website likely isn’t getting that kind of exposure.

Let’s think about why, for a moment; as stated right here in one of our infographics, Facebook remains the largest social media network on the planet, with just over 2 billion users. 

Obviously, those users are going to consume a large share of video content – but it’s more than sheer numbers.

Why Social Media Video Is So Effective

If you’re scrolling through Facebook on a mobile device, like most users are these days, any native video you come across begins playing the moment it enters your screen and continues until the moment it exits a few seconds later. That means, there’s motion on your screen – whatever the content is has a little time to catch your eye before you’re on to the next thing.

If it does a good enough job of catching your eye, you’ll pause and watch some – or all – of the video. If it’s an ad, the hope is you’ll stick around long enough to view the message, the branding, and maybe even click through to the company’s Facebook page. For argument’s sake, let’s say the ad is for a product you feel you could use, so you click through.

Once you’re there, you can see what the business has to offer. They can expose you to the full sales pitch, link you to their homepage, even offer you a way to purchase on Facebook if you want – and they got you there by using video.

You knew all that before, though – it’s why you’re here, trying to determine how you can get others to do your social media video sharing for you. So let’s rewind a bit, back to the moment where the video you were scrolling past caught your eye.

It’s an ad again, but this time, what catches your eye is the video on its own merits, rather than the product it’s selling. You continue watching because whatever it is resonates with you somehow – maybe it’s funny, or touching, or thought-provoking. Maybe it’s just interesting. The point is, you’re into the video before you even see the product or service it’s trying to sell you.

So into it, in fact, you want friends to see it and laugh, cry, or think deep thoughts just like you did. You tag a few friends on the video thread itself, and they go watch the video; maybe a few friends notice the activity in their news feed and watch it too.

Or (better yet, if you’re the business who sponsored it) you share it on your Facebook page or to a group and all 1,374 of your friends have a chance to see it and discuss.

The business, obviously, hopes this activity continues, bringing more exposure for their product or service, more click-throughs to their social media page or website, and more customer conversions from an ad they only had to pay Facebook once to promote – all your shares, likes, and tags were free, in a sense.

Got It. Now, How Do I Do It?

We’ve established that video content on Facebook (we’ll save Twitter, Instagram, Snapchat and YouTube for another day) gets a lot of exposure. With autoplay, even the most boring videos garner at least a few milliseconds worth of a view, but how do you get people to watch your video long enough to get to your brand, your sales pitch, or your call to action? One word:

Entertainment

Facebook has become a news source for many people, but primarily, its roots are in entertainment. When people scroll down their news feeds, they’re more likely to stop on content that interests them. Since most users access Facebook for entertainment purposes, video that’s intriguing in and of itself is more likely to be watched to completion and shared with others.

Users who like a product may still share a video of a product they like – but only if the product is some new, fascinating innovation they feel friends should take a look at. 

If your company sells soap, for example, there’s not a lot of room for soap innovations that shock and wow the public, so you’re better off producing a video that’s interesting on its own merits.

Dr. Squatch, a soap company based in San Diego, did just that. Company founder Jack Haldrup had found an unconventional target market for his naturally made soaps – Midwestern men who wanted to use a natural soap that wouldn’t irritate their skin; unusual, in this case, because that’s the demographic that tends to think natural products are for hippies (to paraphrase Haldrup’s own words).

However, Haldrup knew that this demographic could mean a dramatic boost in sales if only he could draw them in. The problem was that he doubted most were the type to enter “natural men’s soap” into a search bar.

The solution? 

Facebook ads. Specifically, a hilarious Facebook ad that’s been viewed over 12 million times and grew his subscriptions by over 60%, primarily from users running across the ad, having a chuckle, and passing it along to their friends.

Consider companies such as Squatty Potty, with its rainbow-pooping unicorn or Dollar Shave Club, drawing its male base in with a few, well-timed drops of the f-bomb. Those videos were shared far and wide because they made people laugh – they provided entertainment.

So, What about My Company?

Perhaps your company’s brand doesn’t mesh well with humor – crude or otherwise. Consider producing a video that tugs at the heartstrings or features an adorable child saying something precocious you know every mom can relate to – a video worth watching, and sharing, in its own right.

These are the types of video ads you can count on your customer base to share among themselves.

Keep in mind that many users elect to turn off the autoplay feature, so make sure your video graphics are appealing without sound – and entice the user to tap that volume button. And while we’ve been harping on about entertaining videos, make sure you include a clear, visual, call to action so all your new viewers can click through to see what you’re all about.

Make 2019 the year your video ad is the one everyone’s talking about, and sharing with their friends – just remember to make your video worth the watch in its own right, and get your customers to do a little of your social media marketing legwork for you.


avatar

Stephen Moyers is an out of the heart writer voicing out his take on various topics of social media, web design, mobile apps, digital marketing, entrepreneurship, startups and much more in the cutting edge digital world. He is associated with SPINX Digital a Los Angeles web design company & digital marketing agency. When he is not writing, he can be found traveling outdoors with his camera. You can follow Stephen on Twitter @StephenMoyers

The post How to Get Your Social Media Followers to Do Your Video Marketing for You appeared first on SiteProNews.

Using Python to recover SEO site traffic (Part one)

Written by: admin Date of published: . Posted in test

Helping a client recover from a bad redesign or site migration is probably one of the most critical jobs you can face as an SEO.

The traditional approach of conducting a full forensic SEO audit works well most of the time, but what if there was a way to speed things up? You could potentially save your client a lot of money in opportunity cost.

Last November, I spoke at TechSEO Boost and presented a technique my team and I regularly use to analyze traffic drops. It allows us to pinpoint this painful problem quickly and with surgical precision. As far as I know, there are no tools that currently implement this technique. I coded this solution using Python.

This is the first part of a three-part series. In part two, we will manually group the pages using regular expressions and in part three we will group them automatically using machine learning techniques. Let’s walk over part one and have some fun!

Winners vs losers

SEO traffic after a switch to shopify, traffic takes a hit

Last June we signed up a client that moved from Ecommerce V3 to Shopify and the SEO traffic took a big hit. The owner set up 301 redirects between the old and new sites but made a number of unwise changes like merging a large number of categories and rewriting titles during the move.

When traffic drops, some parts of the site underperform while others don’t. I like to isolate them in order to 1) focus all efforts on the underperforming parts, and 2) learn from the parts that are doing well.

I call this analysis the “Winners vs Losers” analysis. Here, winners are the parts that do well, and losers the ones that do badly.

visual analysis of winners and losers to figure out why traffic changed

A visualization of the analysis looks like the chart above. I was able to narrow down the issue to the category pages (Collection pages) and found that the main issue was caused by the site owner merging and eliminating too many categories during the move.

Let’s walk over the steps to put this kind of analysis together in Python.

You can reference my carefully documented Google Colab notebook here.

Getting the data

We want to programmatically compare two separate time frames in Google Analytics (before and after the traffic drop), and we’re going to use the Google Analytics API to do it.

Google Analytics Query Explorer provides the simplest approach to do this in Python.

  1. Head on over to the Google Analytics Query Explorer
  2. Click on the button at the top that says “Click here to Authorize” and follow the steps provided.
  3. Use the dropdown menu to select the website you want to get data from.
  4. Fill in the “metrics” parameter with “ga:newUsers” in order to track new visits.
  5. Complete the “dimensions” parameter with “ga:landingPagePath” in order to get the page URLs.
  6. Fill in the “segment” parameter with “gaid::-5” in order to track organic search visits.
  7. Hit “Run Query” and let it run
  8. Scroll down to the bottom of the page and look for the text box that says “API Query URI.”
    1. Check the box underneath it that says “Include current access_token in the Query URI (will expire in ~60 minutes).”
    2. At the end of the URL in the text box you should now see access_token=string-of-text-here. You will use this string of text in the code snippet below as  the variable called token (make sure to paste it inside the quotes)
  9. Now, scroll back up to where we built the query, and look for the parameter that was filled in for you called “ids.” You will use this in the code snippet below as the variable called “gaid.” Again, it should go inside the quotes.
  10. Run the cell once you’ve filled in the gaid and token variables to instantiate them, and we’re good to go!

First, let’s define placeholder variables to pass to the API

metrics = “,”.join([“ga:users”,”ga:newUsers”])

dimensions = “,”.join([“ga:landingPagePath”, “ga:date”])

segment = “gaid::-5”

# Required, please fill in with your own GA information example: ga:23322342

gaid = “ga:23322342”

# Example: string-of-text-here from step 8.2

token = “”

# Example https://www.example.com or http://example.org

base_site_url = “”

# You can change the start and end dates as you like

start = “2017-06-01”

end = “2018-06-30”

The first function combines the placeholder variables we filled in above with an API URL to get Google Analytics data. We make additional API requests and merge them in case the results exceed the 10,000 limit.

def GAData(gaid, start, end, metrics, dimensions, 

           segment, token, max_results=10000):

  “””Creates a generator that yields GA API data 

     in chunks of size `max_results`”””

  #build uri w/ params

  api_uri = “https://www.googleapis.com/analytics/v3/data/ga?ids={gaid}&”\

             “start-date={start}&end-date={end}&metrics={metrics}&”\

             “dimensions={dimensions}&segment={segment}&access_token={token}&”\

             “max-results={max_results}”

  # insert uri params

  api_uri = api_uri.format(

      gaid=gaid,

      start=start,

      end=end,

      metrics=metrics,

      dimensions=dimensions,

      segment=segment,

      token=token,

      max_results=max_results

  )

  # Using yield to make a generator in an

  # attempt to be memory efficient, since data is downloaded in chunks

  r = requests.get(api_uri)

  data = r.json()

  yield data

  if data.get(“nextLink”, None):

    while data.get(“nextLink”):

      new_uri = data.get(“nextLink”)

      new_uri += “&access_token={token}”.format(token=token)

      r = requests.get(new_uri)

      data = r.json()

      yield data

In the second function, we load the Google Analytics Query Explorer API response into a pandas DataFrame to simplify our analysis.

import pandas as pd

def to_df(gadata):

  “””Takes in a generator from GAData() 

     creates a dataframe from the rows”””

  df = None

  for data in gadata:

    if df is None:

      df = pd.DataFrame(

          data[‘rows’], 

          columns=[x[‘name’] for x in data[‘columnHeaders’]]

      )

    else:

      newdf = pd.DataFrame(

          data[‘rows’], 

          columns=[x[‘name’] for x in data[‘columnHeaders’]]

      )

      df = df.append(newdf)

    print(“Gathered {} rows”.format(len(df)))

  return df

Now, we can call the functions to load the Google Analytics data.

data = GAData(gaid=gaid, metrics=metrics, start=start, 

                end=end, dimensions=dimensions, segment=segment, 

                token=token)

data = to_df(data)

Analyzing the data

Let’s start by just getting a look at the data. We’ll use the .head() method of DataFrames to take a look at the first few rows. Think of this as glancing at only the top few rows of an Excel spreadsheet.

data.head(5)

This displays the first five rows of the data frame.

Most of the data is not in the right format for proper analysis, so let’s perform some data transformations.

First, let’s convert the date to a datetime object and the metrics to numeric values.

data[‘ga:date’] = pd.to_datetime(data[‘ga:date’])

data[‘ga:users’] = pd.to_numeric(data[‘ga:users’])

data[‘ga:newUsers’] = pd.to_numeric(data[‘ga:newUsers’])

Next, we will need the landing page URL, which are relative and include URL parameters in two additional formats: 1) as absolute urls, and 2) as relative paths (without the URL parameters).

from urllib.parse import urlparse, urljoin

data[‘path’] = data[‘ga:landingPagePath’].apply(lambda x: urlparse(x).path)

data[‘url’] = urljoin(base_site_url, data[‘path’])

Now the fun part begins.

The goal of our analysis is to see which pages lost traffic after a particular date–compared to the period before that date–and which gained traffic after that date.

The example date chosen below corresponds to the exact midpoint of our start and end variables used above to gather the data, so that the data both before and after the date is similarly sized.

We begin the analysis by grouping each URL together by their path and adding up the newUsers for each URL. We do this with the built-in pandas method: .groupby(), which takes a column name as an input and groups together each unique value in that column.

The .sum() method then takes the sum of every other column in the data frame within each group.

For more information on these methods please see the Pandas documentation for groupby.

For those who might be familiar with SQL, this is analogous to a GROUP BY clause with a SUM in the select clause

# Change this depending on your needs

MIDPOINT_DATE = “2017-12-15”

before = data[data[‘ga:date’] < pd.to_datetime(MIDPOINT_DATE)]

after = data[data[‘ga:date’] >= pd.to_datetime(MIDPOINT_DATE)]

# Traffic totals before Shopify switch

totals_before = before[[“ga:landingPagePath”, “ga:newUsers”]]\

                .groupby(“ga:landingPagePath”).sum()

totals_before = totals_before.reset_index()\

                .sort_values(“ga:newUsers”, ascending=False)

# Traffic totals after Shopify switch

totals_after = after[[“ga:landingPagePath”, “ga:newUsers”]]\

               .groupby(“ga:landingPagePath”).sum()

totals_after = totals_after.reset_index()\

               .sort_values(“ga:newUsers”, ascending=False)

You can check the totals before and after with this code and double check with the Google Analytics numbers.

print(“Traffic Totals Before: “)

print(“Row count: “, len(totals_before))

print(“Traffic Totals After: “)

print(“Row count: “, len(totals_after))

Next up we merge the two data frames, so that we have a single column corresponding to the URL, and two columns corresponding to the totals before and after the date.

We have different options when merging as illustrated above. Here, we use an “outer” merge, because even if a URL didn’t show up in the “before” period, we still want it to be a part of this merged dataframe. We’ll fill in the blanks with zeros after the merge.

# Comparing pages from before and after the switch

change = totals_after.merge(totals_before, 

                            left_on=”ga:landingPagePath”, 

                            right_on=”ga:landingPagePath”, 

                            suffixes=[“_after”, “_before”], 

                            how=”outer”)

change.fillna(0, inplace=True)

Difference and percentage change

Pandas dataframes make simple calculations on whole columns easy. We can take the difference of two columns and divide two columns and it will perform that operation on every row for us. We will take the difference of the two totals columns, and divide by the “before” column to get the percent change before and after out midpoint date.

Using this percent_change column we can then filter our dataframe to get the winners, the losers and those URLs with no change.

change[‘difference’] = change[‘ga:newUsers_after’] – change[‘ga:newUsers_before’]

change[‘percent_change’] = change[‘difference’] / change[‘ga:newUsers_before’]

winners = change[change[‘percent_change’] > 0]

losers = change[change[‘percent_change’] < 0]

no_change = change[change[‘percent_change’] == 0]

Sanity check

Finally, we do a quick sanity check to make sure that all the traffic from the original data frame is still accounted for after all of our analysis. To do this, we simply take the sum of all traffic for both the original data frame and the two columns of our change dataframe.

# Checking that the total traffic adds up

data[‘ga:newUsers’].sum() == change[[‘ga:newUsers_after’, ‘ga:newUsers_before’]].sum().sum()

It should be True.

Results

Sorting by the difference in our losers data frame, and taking the .head(10), we can see the top 10 losers in our analysis. In other words, these pages lost the most total traffic between the two periods before and after the midpoint date.

losers.sort_values(“difference”).head(10)

You can do the same to review the winners and try to learn from them.

winners.sort_values(“difference”, ascending=False).head(10)

You can export the losing pages to a CSV or Excel using this.

losers.to_csv(“./losing-pages.csv”)

This seems like a lot of work to analyze just one site–and it is!

The magic happens when you reuse this code on new clients and simply need to replace the placeholder variables at the top of the script.

In part two, we will make the output more useful by grouping the losing (and winning) pages by their types to get the chart I included above.

The post Using Python to recover SEO site traffic (Part one) appeared first on Search Engine Watch.

Using Python to recover SEO site traffic (Part one)

Written by: admin Date of published: . Posted in test

Helping a client recover from a bad redesign or site migration is probably one of the most critical jobs you can face as an SEO.

The traditional approach of conducting a full forensic SEO audit works well most of the time, but what if there was a way to speed things up? You could potentially save your client a lot of money in opportunity cost.

Last November, I spoke at TechSEO Boost and presented a technique my team and I regularly use to analyze traffic drops. It allows us to pinpoint this painful problem quickly and with surgical precision. As far as I know, there are no tools that currently implement this technique. I coded this solution using Python.

This is the first part of a three-part series. In part two, we will manually group the pages using regular expressions and in part three we will group them automatically using machine learning techniques. Let’s walk over part one and have some fun!

Winners vs losers

SEO traffic after a switch to shopify, traffic takes a hit

Last June we signed up a client that moved from Ecommerce V3 to Shopify and the SEO traffic took a big hit. The owner set up 301 redirects between the old and new sites but made a number of unwise changes like merging a large number of categories and rewriting titles during the move.

When traffic drops, some parts of the site underperform while others don’t. I like to isolate them in order to 1) focus all efforts on the underperforming parts, and 2) learn from the parts that are doing well.

I call this analysis the “Winners vs Losers” analysis. Here, winners are the parts that do well, and losers the ones that do badly.

visual analysis of winners and losers to figure out why traffic changed

A visualization of the analysis looks like the chart above. I was able to narrow down the issue to the category pages (Collection pages) and found that the main issue was caused by the site owner merging and eliminating too many categories during the move.

Let’s walk over the steps to put this kind of analysis together in Python.

You can reference my carefully documented Google Colab notebook here.

Getting the data

We want to programmatically compare two separate time frames in Google Analytics (before and after the traffic drop), and we’re going to use the Google Analytics API to do it.

Google Analytics Query Explorer provides the simplest approach to do this in Python.

  1. Head on over to the Google Analytics Query Explorer
  2. Click on the button at the top that says “Click here to Authorize” and follow the steps provided.
  3. Use the dropdown menu to select the website you want to get data from.
  4. Fill in the “metrics” parameter with “ga:newUsers” in order to track new visits.
  5. Complete the “dimensions” parameter with “ga:landingPagePath” in order to get the page URLs.
  6. Fill in the “segment” parameter with “gaid::-5” in order to track organic search visits.
  7. Hit “Run Query” and let it run
  8. Scroll down to the bottom of the page and look for the text box that says “API Query URI.”
    1. Check the box underneath it that says “Include current access_token in the Query URI (will expire in ~60 minutes).”
    2. At the end of the URL in the text box you should now see access_token=string-of-text-here. You will use this string of text in the code snippet below as  the variable called token (make sure to paste it inside the quotes)
  9. Now, scroll back up to where we built the query, and look for the parameter that was filled in for you called “ids.” You will use this in the code snippet below as the variable called “gaid.” Again, it should go inside the quotes.
  10. Run the cell once you’ve filled in the gaid and token variables to instantiate them, and we’re good to go!

First, let’s define placeholder variables to pass to the API

metrics = “,”.join([“ga:users”,”ga:newUsers”])

dimensions = “,”.join([“ga:landingPagePath”, “ga:date”])

segment = “gaid::-5”

# Required, please fill in with your own GA information example: ga:23322342

gaid = “ga:23322342”

# Example: string-of-text-here from step 8.2

token = “”

# Example https://www.example.com or http://example.org

base_site_url = “”

# You can change the start and end dates as you like

start = “2017-06-01”

end = “2018-06-30”

The first function combines the placeholder variables we filled in above with an API URL to get Google Analytics data. We make additional API requests and merge them in case the results exceed the 10,000 limit.

def GAData(gaid, start, end, metrics, dimensions, 

           segment, token, max_results=10000):

  “””Creates a generator that yields GA API data 

     in chunks of size `max_results`”””

  #build uri w/ params

  api_uri = “https://www.googleapis.com/analytics/v3/data/ga?ids={gaid}&”\

             “start-date={start}&end-date={end}&metrics={metrics}&”\

             “dimensions={dimensions}&segment={segment}&access_token={token}&”\

             “max-results={max_results}”

  # insert uri params

  api_uri = api_uri.format(

      gaid=gaid,

      start=start,

      end=end,

      metrics=metrics,

      dimensions=dimensions,

      segment=segment,

      token=token,

      max_results=max_results

  )

  # Using yield to make a generator in an

  # attempt to be memory efficient, since data is downloaded in chunks

  r = requests.get(api_uri)

  data = r.json()

  yield data

  if data.get(“nextLink”, None):

    while data.get(“nextLink”):

      new_uri = data.get(“nextLink”)

      new_uri += “&access_token={token}”.format(token=token)

      r = requests.get(new_uri)

      data = r.json()

      yield data

In the second function, we load the Google Analytics Query Explorer API response into a pandas DataFrame to simplify our analysis.

import pandas as pd

def to_df(gadata):

  “””Takes in a generator from GAData() 

     creates a dataframe from the rows”””

  df = None

  for data in gadata:

    if df is None:

      df = pd.DataFrame(

          data[‘rows’], 

          columns=[x[‘name’] for x in data[‘columnHeaders’]]

      )

    else:

      newdf = pd.DataFrame(

          data[‘rows’], 

          columns=[x[‘name’] for x in data[‘columnHeaders’]]

      )

      df = df.append(newdf)

    print(“Gathered {} rows”.format(len(df)))

  return df

Now, we can call the functions to load the Google Analytics data.

data = GAData(gaid=gaid, metrics=metrics, start=start, 

                end=end, dimensions=dimensions, segment=segment, 

                token=token)

data = to_df(data)

Analyzing the data

Let’s start by just getting a look at the data. We’ll use the .head() method of DataFrames to take a look at the first few rows. Think of this as glancing at only the top few rows of an Excel spreadsheet.

data.head(5)

This displays the first five rows of the data frame.

Most of the data is not in the right format for proper analysis, so let’s perform some data transformations.

First, let’s convert the date to a datetime object and the metrics to numeric values.

data[‘ga:date’] = pd.to_datetime(data[‘ga:date’])

data[‘ga:users’] = pd.to_numeric(data[‘ga:users’])

data[‘ga:newUsers’] = pd.to_numeric(data[‘ga:newUsers’])

Next, we will need the landing page URL, which are relative and include URL parameters in two additional formats: 1) as absolute urls, and 2) as relative paths (without the URL parameters).

from urllib.parse import urlparse, urljoin

data[‘path’] = data[‘ga:landingPagePath’].apply(lambda x: urlparse(x).path)

data[‘url’] = urljoin(base_site_url, data[‘path’])

Now the fun part begins.

The goal of our analysis is to see which pages lost traffic after a particular date–compared to the period before that date–and which gained traffic after that date.

The example date chosen below corresponds to the exact midpoint of our start and end variables used above to gather the data, so that the data both before and after the date is similarly sized.

We begin the analysis by grouping each URL together by their path and adding up the newUsers for each URL. We do this with the built-in pandas method: .groupby(), which takes a column name as an input and groups together each unique value in that column.

The .sum() method then takes the sum of every other column in the data frame within each group.

For more information on these methods please see the Pandas documentation for groupby.

For those who might be familiar with SQL, this is analogous to a GROUP BY clause with a SUM in the select clause

# Change this depending on your needs

MIDPOINT_DATE = “2017-12-15”

before = data[data[‘ga:date’] < pd.to_datetime(MIDPOINT_DATE)]

after = data[data[‘ga:date’] >= pd.to_datetime(MIDPOINT_DATE)]

# Traffic totals before Shopify switch

totals_before = before[[“ga:landingPagePath”, “ga:newUsers”]]\

                .groupby(“ga:landingPagePath”).sum()

totals_before = totals_before.reset_index()\

                .sort_values(“ga:newUsers”, ascending=False)

# Traffic totals after Shopify switch

totals_after = after[[“ga:landingPagePath”, “ga:newUsers”]]\

               .groupby(“ga:landingPagePath”).sum()

totals_after = totals_after.reset_index()\

               .sort_values(“ga:newUsers”, ascending=False)

You can check the totals before and after with this code and double check with the Google Analytics numbers.

print(“Traffic Totals Before: “)

print(“Row count: “, len(totals_before))

print(“Traffic Totals After: “)

print(“Row count: “, len(totals_after))

Next up we merge the two data frames, so that we have a single column corresponding to the URL, and two columns corresponding to the totals before and after the date.

We have different options when merging as illustrated above. Here, we use an “outer” merge, because even if a URL didn’t show up in the “before” period, we still want it to be a part of this merged dataframe. We’ll fill in the blanks with zeros after the merge.

# Comparing pages from before and after the switch

change = totals_after.merge(totals_before, 

                            left_on=”ga:landingPagePath”, 

                            right_on=”ga:landingPagePath”, 

                            suffixes=[“_after”, “_before”], 

                            how=”outer”)

change.fillna(0, inplace=True)

Difference and percentage change

Pandas dataframes make simple calculations on whole columns easy. We can take the difference of two columns and divide two columns and it will perform that operation on every row for us. We will take the difference of the two totals columns, and divide by the “before” column to get the percent change before and after out midpoint date.

Using this percent_change column we can then filter our dataframe to get the winners, the losers and those URLs with no change.

change[‘difference’] = change[‘ga:newUsers_after’] – change[‘ga:newUsers_before’]

change[‘percent_change’] = change[‘difference’] / change[‘ga:newUsers_before’]

winners = change[change[‘percent_change’] > 0]

losers = change[change[‘percent_change’] < 0]

no_change = change[change[‘percent_change’] == 0]

Sanity check

Finally, we do a quick sanity check to make sure that all the traffic from the original data frame is still accounted for after all of our analysis. To do this, we simply take the sum of all traffic for both the original data frame and the two columns of our change dataframe.

# Checking that the total traffic adds up

data[‘ga:newUsers’].sum() == change[[‘ga:newUsers_after’, ‘ga:newUsers_before’]].sum().sum()

It should be True.

Results

Sorting by the difference in our losers data frame, and taking the .head(10), we can see the top 10 losers in our analysis. In other words, these pages lost the most total traffic between the two periods before and after the midpoint date.

losers.sort_values(“difference”).head(10)

You can do the same to review the winners and try to learn from them.

winners.sort_values(“difference”, ascending=False).head(10)

You can export the losing pages to a CSV or Excel using this.

losers.to_csv(“./losing-pages.csv”)

This seems like a lot of work to analyze just one site–and it is!

The magic happens when you reuse this code on new clients and simply need to replace the placeholder variables at the top of the script.

In part two, we will make the output more useful by grouping the losing (and winning) pages by their types to get the chart I included above.

The post Using Python to recover SEO site traffic (Part one) appeared first on Search Engine Watch.

9 Tech Tips for Small Businesses

Written by: admin Date of published: . Posted in test

Getting your business dream rolling is not that easy. One needs to have a planned approach in regards to various aspects like budgeting, marketing, manpower hiring etc. If the scale of your business is medium or micro (that is small scale business) then planning and strategizing becomes all the more important.

For a small business (for large scale as well) the real strength is its workforce. The reason is quite simple. A small scale business doesn’t have the capacity to adopt a technology-driven initiative on a large scale and hence rely on labor-intensive routes for enhancing productivity. As a result, Small scale businesses become the net job creator in the economy.

To hire need-specific manpower (an initial step in your business setup process) you have to reach out to those headhunters who are providing manpower solutions on demand. Say for example you require technically efficient manpower then opting for technical headhunters would be the right option.

Technical Headhunters can bring you the desired, skilled and efficient manpower that can add value to your business. Talking about value to the business, technology is one of the greatest resources that you can use to maximize your business.

From marketing and promotion to creating a reach and name for your business you can utilize technology for any number of purposes. Moreover, smart use of technology can also help you in cost-cutting and maximizing the benefits out of available sets of resources. 

So, if you are into a small business operation or are looking to set up a small scale business, then you shouldn’t avoid exploring the benefits of technology. If you are looking for some tips in that regard, then hold on, we have something for you.

Below are some technology tips that you can use to maximize the performance of your business.

Power of the Cloud

Gone are the days’ businesses use files to maintain accounts, important data, and statistics. Today cloud computing is the new king. By shifting the data to the cloud, you ensure that the data is available to all the members of your organization in real-time. 

Moreover, the members of your organization can access the data from anywhere at anytime and make changes as per their needs. One of the benefits is transparency because any change or edit is visible to all members. 

Marketing 

Digital marketing is the word when it comes to promotion and branding these days. Even if you want to reach the potential market/audience within your geographical domain you can’t rely only on offline methods of promotion/marketing.

Technology can be used to give a smart touch to your marketing. Connect with your audience using platforms like Facebook, Instagram, and Twitter and save your time and money on offline channels like hoardings or pamphlets. A good idea is to also get a personalized mobile app for your business, if possible.

E-mail for communication

E-mail is one of the most effective yet underutilized channels of communication. In small (or even large) business operations, you can connect with all the members through emails or the inbuilt chat option (for example in Gmail).

This offers quick, smooth and efficient communication with office workers as well as employees who are in the field. So, use your email effectively.

Effective Management

Effective management and business growth go hand in hand. To manage various aspects related to business like human resource management and operations management, work management technology can be of great assistance. 

Use of Enterprise management software for keeping a track of various aspects related to business is a good idea to keep things streamlined and organized. Real-time data update, management, and retrieval makes it all the more easy for you to manage.

Payment and settlements

Manage all your business related Payment & Settlements through online channels. Be it employee salary processing, payment collection from clients or payment to suppliers/support providers, online channels are the way to go. This saves on costs and allows for the creation and maintenance of E-records.

Skill Enhancement of Workforce

Acquiring new skills is necessary for workers (and your business) to keep pace in a rapidly changing world. Using traditional textbook-based methods is not an option for training your workforce.

Technology can be a great help in this regard. Online modules, video lessons, and simulation software can help in providing a holistic learning ecosystem for office workers. What’s more, employees can continue to learn from home and even during holidays through channels like audio-video lessons.

Connection and Collaboration

Technology can help you in easing the way you connect and collaborate with your clients and partners’. Imagine if you have a client outside your geographical domain and you want to present a proposal to him or want to have a discussion in regards to services offered by you. Video conferencing can be an effective way to do that. 

You can also use this method to connect with your employees or firms/partners with whom you are collaborate.

Hiring

Technology can be a great way to connect with potential employees and to hire them. Platforms like Linkedin offer you a great chance to connect and choose from a number of potential and qualified candidates and thereby save on time and resources.

Customer satisfaction

Technology can help you achieve the highest level of customer satisfaction. Replying to service requests, settling grievances or any customer concerns can be addressed within seconds by technology utilization.

You can create an instant connect with the customer and can ensure your creditability by offering timely and need-based assistance.

We hope these important business tech tips will assist you in modernizing and optimizing your business operation. For any other help, feel free to connect with us.


avatar

Alex Jone is in a HR and Recruitment at Alliance Recruitment Agency- an IT Recruitment Agency. He specializes in helping with international recruiting, Technical Headhunters, staffing, HR services and Careers advice service for overseas and international businesses.
Facebook: https://www.facebook.com/Alliancerecruitmentagency/
Twitter: https://twitter.com/career_alliance

The post 9 Tech Tips for Small Businesses appeared first on SiteProNews.

The Top 9 Free Logo Maker Tools for Small Businesses

Written by: admin Date of published: . Posted in test

Logos are an imperative aspect of any brand and their importance has significantly increased after the digital revolution. Digital platforms have made it quite stress-free for businesses to reach out to their potential consumers yet this has also maximized market competition.  Buyers have hundreds of options for buying a single product and that puts pressure on  businesses because they have to struggle to be the option that most buyers would choose. 

Good marketing and effective branding are the key factors that influence the buying decisions of potential customers. However, both of the following factors rely considerably on the logo. A logo communicates the values of a brand and attracts customers. It delivers meaningful business messages to buyers without speaking a word. A logo is not just a visual representation of a brand, rather it reflects the business identity itself. Therefore, a good logo can contribute a lot to the success of a brand whereas an inappropriate logo can have the reverse effect. 

The benefits of a logo and market competition makes it necessary for a business to have a logo at the outset. Even though logo designing is an expensive industry and many small businesses cannot afford to hire a reputable designer, having a logo is not so difficult anymore. This article is going to present 8 free logo designing tools that can help companies create compelling logos for their brand. A good Free Logo Generator Tool is capable of allowing a business to have a highly functional brand logo in a few minutes. Here are the details of different logo generators that you can access free of cost.

1. Canva

Canva is one of the good free designing websites that provides many designing services. It has many features similar to those available with professional designing tools. It reduces design complexity and makes it easier for businesses to design a logo on their own. The tool provides designers and business with a stock of free images for inspiration. 

2. Design Iconic

Design Iconic is another free logo design maker tool that has a huge range of unconventional features that include patterns, images, icons and a broad color palette. You can easily create your own free logos by simply dragging and dropping your desired – elements, fonts & design concepts to complete your logo. After completing your logo, you can easily download it and the associated files for free to your devices.

3. Logo Makr

Logo Makr is a logo designing tool that is based on the minimalistic design trend. The features that it provides are good for designing a logo with a minimalist look. It provides basic geometric shapes, a variety of fonts and text size, and color options. 

4. UCraft Logo Maker

UCraft provides a free logo making app that can be downloaded on any device. This tool is for businesses who want to have a simple logo. You can choose different geometrical shapes, colors, text boxes, and other features that are available on the app for creating a logo. If you are willing to have a PNG file of your logo, UCraft is the best tool. It allows you to download a PNG file of your logo design. You can utilize the PNG file of your design on different platforms as it is or you can hire a professional just to refine it and use the refined one.  

5. Design Hill Logo Maker

Although Design Hill is also a free logo maker tool that anyone can use, the tool requires you to work through three steps to create a free logo design. The Design Hill site also offers an opportunity for businesses to get their logos designed by other people, but you need to provide them with as much information about your brand as you can. You can design your own logo or you can hire a professional designer, the choice is all yours.  

6. Square Space Logo Maker

Square Space is a logo maker that can compete with human designers because the logos it creates look amazing and professional. Inexperienced designers and small business owners can use the features of the tool without difficulty. The site has an amazing interface that makes working with it even more joyous. Anyone who wants a professionally designed logo but can’t afford it should opt for Square Space because it can provide a professional logo without costing you a penny.

7. Shopify Logo Maker

If you do not want to spend hours on logo designing and want a tool that will facilitate you with a logo within minutes, Shopify is the way to go. Shopify has features that anyone can easily understand regardless of their design skills. It requires no technical skills and you can design a logo within minutes. The template stock is vast and small businesses can avail themselves of unique and compelling logo designs by using images provided by the tool. The good thing is that the template stock keeps growing as new trending logo designs are added all the time. 

8. Graphic Springs Logo Maker

You can create an impressive logo design with GraphicSpring Logo Maker in less than one minute. The tool does not require you to do anything other than entering the name of your brand, selecting a logo category, and picking the image that you want in your logo. Following these three simple steps results in a downloadable logo that you can use on different platforms. The best thing about this design tool is that it allows the designer to preview the logo before downloading it.

9. Hipster Logo Generator

Hipster logo generator is a free logo maker that is based on the Hipster theme. Logos designed with this logo maker reflect the hipster theme. It can be a useful design tool for businesses who want to associate their brands with hipster style. You need no design experience or skills to use this tool. If you do not want to link your business with the hipster movement, however, it is  recommended you not use this tool. 

These are the 9 top logo making generating tools that you can use if you do not want to pay huge amounts to professional designers. You can check out some of these sites and choose to work with the one that you think best suits your business.


avatar

Jessica Ervin is a professional UI UX designer & passionate tech blogger with enthusiastic writing skills. Jessica is a brand researcher as well, She is currently working Design Iconic by which you can easily design your own logos & download it, having a good reader Jessica is contributing to the Technology, Artificial Intelligence, Augmented Reality, VR, Gadgets, Tech Trends and much more. Jessica’s experience has given her an insight of UI UX designing & writing skills and became a conventional contributor. You can follow her on twitter @jessikaervin

The post The Top 9 Free Logo Maker Tools for Small Businesses appeared first on SiteProNews.