Effect Autoblogging Using AI: An Analysis of Marketing Automation

4. 11. 2024
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Author: Alderd J. Froolik, LIGS University, Honolulu, Hawaï, USA
Supervisor: Dr. Roberto A. Llauro, Adjunct Professor of LIGS University

Author Note
Alderd J. Froolik https://orcid.org/0009-0009-1736-7232
Correspondence concerning this article should be addressed to Alderd J. Froolik, LIGS University, p/a Zwanebloem 47, 2408LT Alphen aan den Rijn, The Netherlands. Email: alderd@me.com
Author Biography
Alderd J. Froolik received a Master of Business Administration (MBA) and a Master Of Science (MSc.) both with a major in marketing from EDU Effective in 2023 and graduated summa cum laude (97%) on both masters. He is currently a Doctor of Business Administration (DBA) candidate at Quest Sales & Marketing Automations, under the supervision of LIGS University. His research areas include marketing automations, AI technologies, and low- and no-code tools.

 

In the world of today, many challenges are coming towards SMB (Small and Medium Businesses) owners. One of the biggest challenges is finding the right people to get the job done. Another big challenge is keeping employees motivated. Recurring jobs are not of much help in this challenge. In the world of marketing, consistency is key to helping your customers understand your brand. In the context of social media, when customers have positive interactions with the brand on social media, their satisfaction is improved leading to the desire to buy the brand (Martin-Consuegra et al., 2019; Tran Le Na et al., 2021). Brand awareness will help to decide to buy from your brand. To create brand awareness, you need to post your branded messages repeatedly. This is not only time-consuming but also very repetitive for your employees resulting in reduced productivity, inconsistency, and maybe even loss of interest in their job. All that will turn into less brand awareness, lower sales, and higher employee turnover.

SMBs usually lack of resources to purchase an out-of-the-box solution to fulfill their needs and efforts in posting new and compelling content. These platforms usually have a high price to implement and require additional training of employees who, most of the time need to have some basic knowledge too. Another issue is that most platforms have functionalities that are not needed but must be paid for too or it is missing functionality needed to be getting the job done. Then there is a possibility the employee will turn into an indispensable employee creating a different set of challenges.

Low-or No-code tools are stand-alone applications. These apps are created to make things easier. Most creators of apps are focused and dedicated to get a particular job done; fast, easy and hassle-free. For marketing purposes, there are hundreds of apps available. These apps can be combined so you can create your own, custom-built flow executing various tasks using the same data. Adding or deleting apps is easy, and because of the focus and dedication of their creators, the apps will perform flawlessly.

This study will show the effect of these apps on productivity and the effect on marketing itself to assess the following research question:

Automated blog posting; the correlation between number of posts and reach/traffic.

Hypotheses

The outcome of the question likely is that the effect of implementing low- and no-code tools will increase traffic and show a significant increase in brand awareness through the chosen social media channels, the content feed, and the number of apps used. The hours spent on repetitive jobs will show a reduction and, as a result of the consistency in the blogposts, the timely posts, and the use of hashtags, the Search Engine Optimization (SEO) score will show an increase.

Method

The methodology employs quantitative research. On the used channels the automated AI-generated blog is posted, and relevant hashtags are added at the bottom of each post. Hashtags on social networks promote social integration and the joint expression of ideas. (Skivko M.O., Korneeva E.N. et al, 2023). In this method, the data from the used social media platforms is gathered and collected in Google Sheets Online databases. The collected data is the reach and the number of blogposts in a 7-day interval.

Context

The participants are two dropshipping webshops. Both carry the same products from the same vendor. Both webshops operate on the same shopping cart software (Shopify) and use the same software. Both webshops hold about 100,000 items in their catalogs. The only difference is the brand. Each webshop is using the same social media platforms. The webshop using just paid advertising is solely used as a reference point for SEO results.

Participants

Webshop #1 is using paid advertising on the Google Shopping network and is operating the webshop purely by hand. The blogposts are generated by ChatGPT in a bi-weekly frequency and posted by hand on the selected social media channels. The images are created by hand in Canva, a DPT tool. Each created blogpost is manually uploaded to the selected social media channel, creating duplicated content over the selected social media channels. The age of the used domain is 5 years. The webshop was started in September 2023.

Webshop #2 does not use paid advertising. It has a product feed to Google Shopping which is free of costs. The blogposts are generated by ChatGPT daily for each social media channel, avoiding duplicated content. Also, the content of the catalog is used to create content automatically by re-writing it by using ChatGPT into an ad for each social media channel and posted fully automated on a 59-minute schedule during working hours. The domain was new at the start of the webshop in October 2023. For this research, the automations are set up for webshop #2.

Automation setup

The automations are built on the platform Make.com, formerly known as Integromat. Make.com is an online automation platform that enables users to integrate and automate workflows between various apps and services. It provides a visual interface for creating connections and setting up automation scenarios without the need for coding. Make.com allows users to connect different applications, databases, APIs, and other online services to create automated workflows, data synchronization, and task automation. It helps businesses streamline their processes, save time, and improve productivity and consistency by automating repetitive tasks and data transfers between different systems. The apps used for this automation are the RSS feed, ChatGPT, WordPress, Pinterest, Instagram Business, Facebook, and LinkedIn apps.

For each type of post, a custom automation is built where the participant has repetitive work and/or lack of time to perform blogging/posting during their normal business hours. Blogposts are #3 on the highest ROI (Hubspot Marketing Trends, 2023). Therefore, the blogpost automation will run every day at a set time. Also, the blogposts are posted on webshop #2 under the “news” section. The post with catalog content is running every 59 minutes each day from 7 AM to 7 PM and includes a direct link to the item in the catalog. Over 5-months 1,403 Facebook posts, 1,400 Instagram posts, 23,982 Pinterest pins, and 794 LinkedIn posts were automatically created.

Measures

For the quantitative data collection, the measures of the experiments are taken from the data of the used social media channels. For each channel and each participant, the data is added to a Google Sheets spreadsheet. The data consist of:

LinkedIn views                              The number of views on the LinkedIn corporate page

#post LinkedIn                              The number of posts on the LinkedIn corporate page

Instagram accounts reached              The number of accounts reached on the Instagram business account

#post Instagram                            The number of posts on the Instagram business account

Facebook post reach                    The number of accounts reached on the Facebook corporate page

#post Facebook                            The number of posts on the Facebook corporate page

Pinterest audience                       The number of audience reached

#pins Pinterest                              The number of pins placed on Pinterest

Procedure and Analysis

For the quantitative results, the statistics were taken every 7 days during the experiment over 5 months. Only the data of webshop #2 was measured as webshop #1 is only a reference point for the SEO results. Also, only webshop #2 had the automations set up and running.

Results

The correlation analysis between cumulative posts and cumulative visits (used as a proxy) reveals a correlation coefficient of approximately 0.98. This indicates a very strong positive relationship between the two variables, suggesting that as the cumulative number of posts increases, the cumulative number of visits (proxy) also increases significantly as shown in Chart 1. The scatter plot visually supports this analysis, showing a clear positive trend between cumulative posts and cumulative visits. The data points are closely aligned along a path that indicates a direct correlation, and the correlation coefficient near 1 reinforces the strength of this relationship. This analysis strongly supports the argument that posting frequently on social media channels can be highly effective in increasing engagement and visits, which is a compelling reason for businesses to invest in an active social media posting strategy.

Chart 2 illustrates the growth over time of both the cumulative posts and the cumulative reach on Facebook (in blue and red) and Instagram (in green and purple), demonstrating the positive trend in engagement because of social media activity.

Chart 3 illustrates the growth over time of both the cumulative posts and the cumulative reach on LinkedIn (in blue and red) and Pinterest (in green and purple), also demonstrating the positive trend in engagement because of social media activity. This visual representation, along with the cumulative data, supports the conclusion that consistent posting on these platforms correlates with increasing reach and potential visits.

Discussion

My research is to determine the effect of automation of blogposts and content with the use of Artificial Intelligence in high volumes. When an ai blogpost writer re-writes the catalog content like products and categories, specific for each social media channel a high volume of content can be created and distributed to the assigned channel automatically. The effect is also shown in SEO research. Webshop #1 is solely relying on paid Google Shopping and distributes a bi-weekly blogpost vs. webshop #2 on massive content distribution as shown in the results in chart 4 and chart 5. If the high number of posts are continued page authority will likely increase as well as the number of organic keywords. Also, E-commerce optimization with the implementation of social media and SEO techniques to boost sales in retail business (Mohammad & Hoque et.al 2020).

Limitations of the Present Study

The conclusions from this study have some limitations. For one, the results are based on 2 webshops. To find participants to conduct similar research is impossible due to the unknown of the effect. A second limitation is the number of participants. Because the AI solution is new most stakeholders are not open to participating in the experiment. A third limitation is, that Pinterest is a different social media channel that works with pins, therefore the results are set in a different chart. Same as LinkedIn targets B2B. The fourth limitation is that the research should ongoing process but was capped to 5 months. The last limitation is that for each webshop the outcome can vary. Specific targeting, limitations on the number of items in the catalog, geographical limitations, etc. have an impact on the results.

Conclusion

              The cumulative data analysis and corresponding correlation coefficients for Facebook, Instagram, LinkedIn, and Pinterest all indicate very strong positive relationships between the cumulative number of posts and the cumulative reach on these platforms. The correlation coefficient, represented by these numbers, quantifies the strength and direction of the linear relationship between two variables. In this context, the variables are the cumulative number of posts and the cumulative reach (or visibility. Here's what the correlation coefficients indicate:

Value Range

The correlation coefficient ranges from -1 to 1.

-1 indicates a perfect negative linear relationship: as one variable increases, the other decreases proportionally. 0 indicates no linear relationship: changes in one variable do not predict changes in the other. 1 indicates a perfect positive linear relationship: as one variable increases, the other also increases proportionally.

Strength

The closer the coefficient is to -1 or 1, the stronger the linear relationship between the two variables. A coefficient close to 0 suggests a weak or no linear relationship.

Direction

A positive coefficient (closer to 1) means that as the number of posts increases, the reach also tends to increase, indicating a positive association. A negative coefficient (closer to -1) would indicate that as one variable increases, the other tends to decrease, but this is not the case in our analysis.

Here are the conclusions for each platform:

Facebook Analysis

With a correlation coefficient of approximately 0.988, the data suggests that increased posting frequency on Facebook is strongly associated with increased reach. This implies that consistent posting is likely to improve visibility and user engagement on Facebook.

Instagram Analysis

Similarly to Facebook, Instagram also shows a correlation coefficient of approximately 0.988. This strong positive relationship indicates that posting more frequently on Instagram can significantly enhance the reach of content and, by extension, potentially increase visits to the webshop.

LinkedIn Analysis

LinkedIn exhibits an extremely strong correlation, with a coefficient of approximately 0.999. This almost perfect positive correlation suggests that posts on LinkedIn are highly effective at increasing reach, implying that LinkedIn could be a particularly valuable platform for engaging with a professional audience and increasing visibility.

Pinterest Analysis

The correlation coefficient for Pinterest is approximately 0.991. The strong positive relationship between pins (posts) and impressions (reach) suggests that active pinning contributes to greater content visibility and user interaction on the platform.

In conclusion, the analysis demonstrates that a very active and consistent posting strategy across social media platforms can be highly effective in increasing reach and traffic. For businesses, especially those not utilizing paid advertising, leveraging these platforms for content distribution is a powerful way to engage with audiences, increase brand visibility, and potentially drive more traffic to their main websites or webshops. Implementing automations reduces the labor to almost zero. The labor hours saved reduce the costs per acquisition (CPA) significantly.

Further research

The posts were all based upon re-written texts with static images or photos. In further research on automated blog posting with the use of AI-generated video content could reach an even larger audience. In the modern days, advertising is still the main business model in the short video industry (Jiang, L. and Zhang, H. 2020). The same high-volume content posting on video-based social media channels like YouTube Shorts, TikTok, Reels, and Stories, will likely show similar results with a broader reach to be expected. Make.com and a range of tools can create a video from catalog item images which then can be posted on the video-based channels; all automatically.

References

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