Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

How Web Scraping Can Empower Marketing in 2022

There’s a lot of buzz and excitement around the combination of digital marketing and web scraping. Data has always been the driving force behind marketing strategies, so the arrival of something that can get external data is welcomed with open arms. I don’t think the industry has quite figured out how to use web scraping for marketing. Sure, there’s a lot of information out there on how it may be beneficial, but most of it oversells the idea. In my eyes, web scraping plays a supporting role in the development of strategies rather than being something of critical importance.

With that in mind, we should be looking towards how it can improve everything else. If there’s something completely new we can do with web scraping and marketing – great. But it’s easier to start with baby steps.

Top MarTech Update: Pinterest Introduces New Pinterest APIs to Improve Shopping Experiences

What, where, and when

If we were to truncate web scraping down to a single sentence it would be – a process that can collect any public online data on the internet without manual work.

Marketing departments can get hyped up just as easily as they can hype others up. It’s unsurprising, therefore, that the idea of automated data collection quickly takes hold of most people working in the area. Getting data about anything from anywhere with instant results seems enticing.

Once the process is up and running, soon you realize that it’s not all fun and games. What usually arrives is a garbled mess of potentially highly valuable information. Working with it is challenging, however, that’s one of the reasons why companies hire data analysts.

Additionally, the data might seem useless. For example, scraping a competitor’s blog or other website sections seemingly provides little value. There are all the posts and other content, but there are no insights to extract.

That’s our first lesson – web scraping for marketing is a little different. Other use cases such as dynamic pricing can utilize the extracted data instantly. They can apply everything right when they get it. Marketing, on the other hand, requires more data, mostly of the historical kind.

In-depth logging has to be done. A lot of what web scraping can deliver is semantic data. In other words, it’s regular sentences – thoughts, writings, and musings of other people. Getting to the nuggets isn’t as simple as extracting numerical SEO data from an Excel spreadsheet. Utility becomes apparent once lots of data have been collected from different periods.

Not a step without competitor monitoring

Everyone harps on about competitor monitoring and how important it is. Most of it revolves around following the products and services being sold, pricing, and, possibly, some other important changes.

Related Posts
1 of 2,185

Marketing, however, has a unique opportunity provided by web scraping. Previously, if you wanted to find out the exact inner workings of a competitor’s approach to marketing, find all the trials and tribulations they experienced along the way, and the changes they had to make, the best way was to get employed by them. Not the best strategy, to say the least. You might think it impossible to reverse engineer the details of a business’s marketing strategy just from the content, advertisements, and other data they put out. Yet, SEO specialists would say they have gotten fairly close to understanding the primary concepts of Google’s algorithm.

I might be embellishing the achievements of SEOs a little bit, but I think it still stands to reason that with close competitor monitoring you could reverse engineer a lot of what they do for marketing. It’s not just for looks, either. A competitor’s marketing strategy’s value is immense. Gaining an idea on what they are doing marketing-wise is not only a chest of ideas. It gives a ballpark on how well your own marketing strategy is doing as it’s often hard to evaluate. Additionally, it gives a proper inside look on how they might develop other business channels.

Use of Web Scraping in Content strategy and Beyond

Content marketing is awfully hard to measure. They serve as a secondary role to most other departments as they lead prospects down the journey but are rarely the turning point. Everyone gets the idea that content is important, yet no one has a clear answer on why and how.

The mystique surrounding content marketing doesn’t do it any service as optimizing the process can sometimes be seen as some esoteric ritual based on SEO guidelines. Even worse, results can be wildly different even if the content is seemingly good. Without the use of public web scraping solutions such as SERP scraper APIs, getting a grip on what’s going on would be difficult.

While it can be hard to draw conclusions, a lot can be learned using web scraping. Take content pieces that rank well in results from a competitor and match them against the same (or similar ones) of your own that rank badly. Extract all the data from them and start comparing.

Such data can then be analyzed to find weaknesses in aspects of the copy. There can be numerous factors that influence readers to invest more time in the article. A frequent occurrence is the overuse of fluff – information the reader is already familiar with or that is useless altogether.

In the end, collecting content marketing data gives a good way to understand how well writers and SEOs are performing, and provides lots of learning material for both.

Conclusion

Scraping for digital marketing should play a supporting role rather than attempt to occupy the center. Use it to generate external data that puts things in perspective, gives ideas, and ample opportunities for improvements.

Recommended Post: Top Programming Languages for Every DevOps Engineer

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.