Skip to main content

Hadoop Data Mining Tools Can Enhance The Value Of Digital Assets

The digital marketing field has become far more datacentric in recent years. Before the turn of the century, the reliance on data technology was little more than nonexistent. It was primarily limited to handling the backend computations needed to handle the bandwidth of large websites. Web developers utilized data to some capacity as well, but marketers rarely considered doing so. This has changed in the 21st Century.

The tides have changed in more recent years. Big data has become critical to the evolution of digital marketing. Hadoop technology is helping disrupt online marketing in various ways.

One of the ways that Hadoop is helping the digital marketing profession is by increasing the value of digital creatives. Digital marketers can use data mining tools to assist them in a number of ways. Some of the benefits are detailed below:

Optimizing metadata for greater reach and branding benefits

There are a number of variables that affect the ROI of digital marketing creatives. One of the most overlooked factors is metadata.

Metadata is important for numerous reasons. Search engines crawl metadata of image files, videos and other visual creative when they are indexing websites. This data can play a very important role in SEO. Websites that use metadata properly will perform a lot better in the SERPs.

Hadoop tools are able to help marketers improve their metadata. They can use this technology in several ways:

  • They can mine metadata and perform regression analysis on it. They can see patterns between different metadata formats and performance. One example is identifying the relationship between SERPs and keyword density or the presence of certain target keywords.
  • Hadoop tools can help find metadata from other creatives on competitor websites or assets in other niches. This can inspire new ideas for structuring their own metadata, which can make things easier if they don’t want to develop it from scratch.
  • Hadoop data mining technology can identify duplicate metadata content across different digital creatives, which might be causing search engine penalties, message saturation issues and other problems. Marketers can resolve the issues with duplicate metadata and see better results.

Metadata is important in digital marketing. Marketing should use Hadoop technology to leverage it to its fullest potential. Furthermore, it’s important for every business to utilize a digital asset management solutions to help them manage their branding assets properly. These assets include everything from logos to metadata to typography to and color palettes.

Monitor engagement statistics in a more nuanced way

Every marketer should focus on maximizing engagement of their best creatives. Traditional analytics interfaces can provide a rough snapshot of engagement, but ones that use Hadoop are more effective.

The trouble is that this analytics approach rarely tells the full story. You need to use data mining tools that provide more granular insights.

Hadoop tools can find data on more variables that helps optimize engagement much better. Tailwind has a detailed analytics interface that helps marketers determine keywords, geography and other variables that influenced the number of clicks, saves and other engagements that digital assets received. Some platforms help YouTube marketers determine the CTR of thumbnails, which is an important variable in improving their performance with the YouTube algorithm. This helps marketers get a much higher ROI by being able to pare Creatives with the right traffic sources.

Brainstorming ideas based on third-party Creatives

The development of digital Creatives is often a number’s games. This is especially true with Pinterest, where a marketer can create several hundred pins and find that only 10 of them drive the vast majority of their traffic. This explains the reliance of big data for Pinterest and Instagram marketers.

Unfortunately, creating such a large quantity of digital creative can be overwhelming. Marketers need to find inspiration from many different sources to generate enough content to thrive.

This is one of the biggest benefits of Hadoop technology. They can use it to mine data from various marketing campaigns, both inside and outside their industry. They make find information about lots of other digital creative, which they can use as models for their own content marketing strategy.

Hadoop Technology is invaluable to digital asset creation and optimization

The benefits of big data in the digital marketing profession cannot be overstated. While the creation and storage of big data is crucial, this data is useless if it cannot be extracted for optimization purposes. Shrewd marketers recognize the need to use Hadoop technology to create more effective digital assets and match them to their target audience.

The post Hadoop Data Mining Tools Can Enhance The Value Of Digital Assets appeared first on SmartData Collective.



from SmartData Collective https://ift.tt/3lcgWlE
via IFTTT
Labels:

Comments

Post a Comment

Popular posts from this blog

Controlling legend appearance in ggplot2 with override.aes

[This article was first published on Very statisticious on Very statisticious , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. In ggplot2 , aesthetics and their scale_*() functions change both the plot appearance and the plot legend appearance simultaneously. The override.aes argument in guide_legend() allows the user to change only the legend appearance without affecting the rest of the plot. This is useful for making the legend more readable or for creating certain types of combined legends. In this post I’ll first introduce override.aes with a basic example and then go through three additional plotting scenarios to how other instances where override.aes comes in handy. Table of Contents R packages Introducing override.aes Adding a guides() layer Using the guide argument in scale_*() Changing multiple aesthetic par...
Post a Comment
Read more

Using RStudio and LaTeX

(This article was first published on r – Experimental Behaviour , and kindly contributed to R-bloggers) This post will explain how to integrate RStudio and LaTeX, especially the inclusion of well-formatted tables and nice-looking graphs and figures produced in RStudio and imported to LaTeX. To follow along you will need RStudio, MS Excel and LaTeX. Using tikzdevice to insert R Graphs into LaTeX I am a very visual thinker. If I want to understand a concept I usually and subconsciously try to visualise it. Therefore, more my PhD I tried to transport a lot of empirical insights by means of  visualization . These range from histograms, or violin plots to show distributions, over bargraphs including error bars to compare means, to interaction- or conditional effects of regression models. For quite a while it was very tedious to include such graphs in LaTeX documents. I tried several ways, like saving them as pdf and then including them in LaTeX as pdf, or any other file ...
Post a Comment
Read more