From a marketing perspective, organic traffic is not just limited to SEO. Conversely, it covers a wide range of traffic sources as long as the majority percentage of investment is focused on manpower. They can be social media, partnership, VoD, email and so on. Compared to these channels in terms of organic traffic, email marketing is still the most efficient approach in one-to-one conversation marketing with a higher new customer conversion rate and lower cost per retention notably in the eCommerce and B2B sectors.
Basically we have two options out there if leveraging the magic of email marketing – Paid and Free platform. If a long term investment return is your preference rather than you being restricted by the platform recurring payment fees, this article can fit your stomach.
This piece expands on how to save 90% of your manual email marketing campaign time by using Gmail and Python script. By the end of this article, you and your team can write a Python script to build an email blast system using Gmail.
This python tutorial is relevant to coach how to automate your Python applications with the Google cloud platform. Compared to local device crontab and cron jobs, Cloud platforms like Google can allow your application 24 hours and 7 days stand-by and run by triggering preset events. You need to either keep the laptop running 24 hours or sit beside the device to monitor. I will take the trending topic bot for example and walk you through all components and script codings.
In this Python Tutorial, I would walk you through how to build a trending topic bot using Tweepy and Google News. By the end of this tutorial, you can learn the logic, framework, and mindset of building this bot. You can roll out localized versions based on what markets your business is entering.
In this Python Tutorial, I would talk about how to create price trackers for three popular retail marketplaces or channels from an eCommerce seller perspective. In this tutorial, we would use some modules listed as below and by the end of it, you can use a tracker built by yourself. Refreshing a dashboard every morning can become part of your lifestyle that relieves your busy work.
Keyword volume and CPC are very familiar terms as long as you are running digital marketing campaigns and doing performance prediction. I believe it’s a critical signal to deploy content, budgeting between organic and paid media ads, and also evaluate a business investment. It’s because it represents the low funnel opportunities in a way.
However, it’s a pity in terms of keyword volume and CPC research that there are 3 challenges you might have experienced – Free lunch is not free, people manually input and download, and 3rd party software is experienced. So this article is a method to resolve this issue.
Automatic chain effect supplier is a nice phrase to describe the youtube data source. Most popular video content in SERP, active and famous Youtube channels, and the contact points such as email, website and social channels are in place as long as the youtubers add on. Basically people are able to grab content ideas, youtuber profile and automate outreach from every time of youtube bot scraping command.
Business dashboard is a must-have thing nowadays if you are running an online business. Connecting with different platforms and consolidating diverse data into one place, does help you understand a better picture. Of course, making a more proper and better decision can’t happen without an organized and up-to-date date in the dashboard.
SEO keyword insight is pretty valuable for any webmasters. The existing ranked keywords’ avg position performance month by month let you understand how’s going of your content marketing strategy. What is more, new keywords popping up in the search console inspire you with the new content perspective and long-tail keywords to utilize. It’s kind of a no-brainer, but the thing is how to organize the process and automate the process which grabs the SEO insight. This is the value you can gain from this piece.
I believe we can’t live without search engine channels in life and work. Depending on countries, Google, Yahoo, Naver, Baidu, and so on have been part of the body. Every coin has two sides because marketers might be suffering from overusing search engines to research the market and competitor information. We’re feeling dizzy while watching the screen in front of the laptop for a long day at work.
In this article, I would introduce you to a way to scrape all search result information by using Python, Pandas, Google custom search API, and CSE (custom search engine). By the end of this article, you just need to add keywords, you can find potential publishers, bloggers, competitors, and popular content, download the images, etc, and store the information with title, landing URL, and so on information into a local CSV.file.
In the previous Python Tutorial for digital marketers, I talked about leveraging Shopify APIs to scrape the competitors’ product feed and monitor up-to-trend products and pricing from there, for the purpose to adjust tactics and keep your business cutting-edge from the same selling marketplaces.
In a way, the product feed is not sufficient to understand the market demand, because you might not want to anchor a dot, where they’re selling low-demand products, or the product trend has been going down. Then, unfortunately, you test along with these sellers and lose money at the end, because you just follow without further step analyzing the big picture.
The big picture is critical in the business battleground, and the end consumer search trend is a key implication to tell you how’s the demand going out there, and what topics they are looking for.
In this piece of Python Tutorial, I would walk through how to pull search data from Google Trends API via Pytrends, then people can learn the data that is integrated with your in-house database, and identify the opportunities. By the end of this Python Tutorial, you can master how to install Pytrends and necessary modules, what available API methods and parameters you can leverage to scrape available data, and custom the data sheet based on actual needs.
In the previous Python Tutorial, we talked about how to scrape more than 50 videos from a Youtube search query keyword, and also grab the performance of each video, such as view, comment, like, etc. However, it’s not the end of automation power, like saying you aim to research, filter Youtubers, and automate the collaboration invitation process. At least, the fetched list of Youtubers should be saved and managed in a datasheet on a cloud drive instead of in the CSV file, that can be set up and easily integrated with other platforms.
So in this Python Tutorial, I will continue to use the Python script from the Python Tutorial Chapter 6, and walk you through how to create a Robot user account, leverage Google Sheet API to save all fetched data in a Google Sheet In your web scraping python script. By the end of this Python Tutorial, you can learn what modules you need to set up, and experience just looking at a spreadsheet that is automatically listing all videos in a preset format.