Ravi Shankar Prasad, India’s IT and Law and Justice minister, has accused Facebook India’s leadership team of suppressing the reach of pages that support and promote right-leaning ideology, in what is the latest turn of events for the social giant in its biggest market by users where it has also been accused of showing favoritism to Prasad’s ruling party.
In a letter to Facebook co-founder and chief executive, RS Prasad wrote that he has learned that ahead of the general elections last year, the social giant’s India management team, in a “concerted effort,” deleted or substantially reduced the reach as well as “provided no recourse or right of appeal to pages” that were supportive of the right-of-centre ideology.
“The above documented cases of bias and inaction are seemingly a direct outcome of the dominant political beliefs of individuals in your Facebook India team,” the minister wrote in the letter, without elaborating those cases. He said the ruling, right-of-centre, Bharatiya Janata Party wrote “dozens of emails” to Facebook’s management team and received no response.
Prasad also accused some unnamed Facebook employees of abusing Prime Minister Narendra Modi and other senior ministers of BJP “on record.”
He characterized this alleged behaviour as “problematic.” “It is doubly problematic when the bias of individuals becomes an inherent bias of the platform. And it is unacceptable when political biases of individuals impinge on the freedom of speech of millions of people,” he added.
Prasad’s letter today comes as Ankhi Das, a top-level Facebook executive in India, has been accused of showing support to Narendra Modi before he was elected as Prime Minister in 2014 and disparaging the opposition party, Indian National Congress.
According to The Wall Street Journal, Das had also opposed applying the company’s hate-speech rules to a member of Indian Prime Minister Narendra Modi’s party because she worried taking any punishing actions would hurt the company’s business prospects in India.
Politicians from both the sides have slammed Facebook for showing favoritism in India. In the letter, Prasad characterized these reports to be based on “selective leaks” by some Facebook employees to “portray an alternative reality.”
On Tuesday, local newspaper Indian Express reported that ahead of last year’s polls, BJP flagged a list of 44 pages opposed to the party, claiming they were “in violation of expected standards” and carried posts “not in line with facts.” At least 14 of those pages are no longer on the platform. The report claimed that Facebook’s India team was responsive to BJP officials.
5 Effective Ways to Run Facebook Ads A/B Tests
Facebook Ads A/B Tests or split tests help them try different versions of ads with various campaign elements. This process helps them arrive at the best version for the organization’s target.
A/B Tests offer a vast pool of resources to try out various versions. You may get caught up and lose your way to arriving at the best version in a limited time. To better understand this topic you can read the Facebook ad testing guide. Here are five effective ways to run Facebook Ads A/B Tests-
1) Start with the minimal number of variables
This approach will help you analyze the impact of a variable much better. The lesser the variables, the better will be the relevant results and more conclusive. Once you have various versions, you will need to run them through the A/B Significance Test to determine if the test results are valid.
2) The second way is to select the correct structure.
There are two structures in A/B tests. One is a single ad test, and the other is multiple single variation ad sets. All the variations will go under one ad set in the first structure. Each variation will be under a separate ad set in the second one. Out of the two, the second one works out to be better and gives better results.
3) Use of spreadsheets is important to stay organized.
These spreadsheets help collect and analyze data to get meaningful insights and arrive at data-backed decisions.
4) Do target advertising and set realistic time goals.
One approach is to choose an entirely new set of audiences. Also, the data pool should be vast and not the same as some existing campaigns. The reason for choosing a different audience is that Facebook may mix up your ads and give contaminated output.
Another approach to choosing the right audience is to pick geography. It works better, especially when you have business in a particular region.
It’s also essential to set a realistic timeline for your testing. Facebook suggests one should run a test for at least four days, but you can choose to run the test for up to 30 days.
5) Set an ideal budget.
The concept of a perfect budget is subjective. But, you can fix it yourself, or Facebook can do that for you based on your testing data. A large part of the test budget is spent on avoiding audience duplication. If the same audience sees variations, it could affect the test results.
Besides these top five effective ideas, you will need to take a few more action points to make the testing process efficient. Make sure you put the website’s domain link and not the landing page link in the ad, as that doesn’t look good. Put appropriate Call To Action Button, such as ‘Learn More,’ ‘Buy Now,’ etc. It’s also important to see how your ad is coming across on various electronic gadgets- mobile, tablets, etc.
Another strategy that works is trying to engage the customer. You may add social engagement buttons such as ‘Like’ or ‘Comment.’ Use high-resolution images as they work better with the customers. Low-quality, highly edited images are often not liked and trusted by the consumers.
You can learn more about the audience behavior patterns with A/B test results. Conducting these tests on Facebook streamlines the entire process and makes it smooth for you. With the test results, advertisers and marketers can work on the creatives they need to utilize.
To sum it up, you can run an effective A/B test campaign within the specified budget. You don’t need to spend massive amounts to get your advertisement right. You’ll make the correct assumptions about the performance of variations with a good understanding of business and consumers.
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