Nov 23, 2018

Facebook Has Changed, and Your Digital Strategy Has to Adjust

Not a long time ago, Facebook made one of the most shocking announcements. It decided to remove Partners categories from the advertisement interface. While marketers are juggling to create and edit their existing campaigns, Facebook is set to roll out a few more changes. After the incident of the Cambridge Analytica fiasco that exposed how Facebook shares the personal details of its users to businesses, it has made the platform to improvise its advertisement interface. Given all the changes happening, it is imperative for marketers at a digital marketing agency in Virginia Beach to revise their digital strategies and approaches.

For instance, while using ‘Custom Audience Targeting’ for running any ad campaign, marketers will not be able to see the estimated audience-reach anymore. Since the feature allowed advertisers to create custom audience by exploring any targeted-audience sector and understand the market trend better,  the shift is surely going to affect brands’ and businesses’ reach adversely. 

As per digital innovators, this move by Facebook reflects its commitment towards making the platform more private in terms of advertisement. So, how can digital marketers adjust to the changes happening on Facebook? Here are some ways:

Adhere to new terms and condition

When using 'Custom Audiences' to upload a new set of custom audience, it is a must to accept the Terms and Conditions to ensure that your brand has the consent to use the data.

Goodbye, Partners

Through the Partners categories, advertisers previously could target audiences based on 3rd party data. It allowed integration of ad campaigns across mediums. After the move to remove the categories, businesses that rely on information such as credit cards, ownership and investment would need to reframe their marketing strategy. By using lookalike audiences feature, such businesses can prevent loss of traffic on their platform.

Audience sharing

To avoid losing all of your online audiences, it is now a must to set up an audience-sharing connection with the new Business manager before you share any account with a Facebook Ads.

Information sourcing

Since Facebook is more focused on keeping the information of its users more private than ever, it is a must for brands to align with Facebook’s new transparency standards. Advertisers and marketers are now required to share the source of the audience they are targeting through Custom Audience Certification Tool. Before targeting the audience group, it is now essential for the brands to specify whether the audience data was collected or acquired through shared partners.

On the users’ front, they would know why they see a particular ad, and unless they don’t agree to be a part of customer audience list, marketers can’t include them in their audience list.

But the changes in the Facebook advertising algorithm are not all about downfall for advertisers. There are two significant advantages for marketers. The first and foremost thing is that Facebook generates a majority of its revenue from mobile advertising thus it cannot afford to lose advertisers. Besides this, advertisers can collect consumer data by deploying look like audience search strategies. 

Oct 17, 2018

How is Artificial Intelligence impacting Digital Marketing?

The use of artificial intelligence and machine learning is not limited to the world of IT, but digital marketers and innovators are increasing. It is evident from a survey that included over 1,600 digital marketing professionals out of which 61% cited that AI and machine learning will be used for data analysis in the coming years. Owing to this trend Virginia digital marketing companies and the likes elsewhere have started using these two technologies in their marketing efforts.

As the amount of consumer data keeps on growing, IT related techniques will significantly affect the digital marketing solutions offered by digital marketing agencies. But how will this become possible? Read on to know.

Predictive Analysis

The predictive analysis takes in use the data and techniques of machine learning techniques to predict the probability of a future event. This model can be used in various areas including marketing. By predictive analysis, it becomes easier to predict the possibility of a prospect turning into a client. Not only this, but the predictive analysis also helps brands to predict the behavior of the consumer and the stimuli to make a purchase.

Digital Advertising

So far, digital advertising has adopted the technique of artificial advertising most successfully. Google ads and Facebook are already using AI to look for people who are more likely to take the desired action. Brands analyze the information updated by the users of these social media channels like what they like, where they reside, etc. to spot the ideal audience for the brand.

Google AdWords has adopted machine learning and AI through an automated auction-based system that allows advertisers to bid for the lowest CPC plan.

Content Curation

The most significant advantage AI and machine learning have on content development are that it not only can generate content but also curate it. Content curated by AI has a considerable potential to initiate the conversation between the brand and its consumers while offering them relevant and customized content.  Digital innovators are using the power of AI to create a personalized content recommendation to entice their interest in certain products. For instance, Netflix gives the recommendation of movies and TV serials based on the history of the viewers.

Email Marketing

Businesses are exploring the power of AI and Machine Learning for created personalized emailers and e-mail marketing campaigns. These campaigns and strategies are formulated based upon the consumers’ behaviors and their preferences. Offering personalized emailers facilitates a better connection between the brand and its consumers. It is a very effective way to turn a prospective visitor into a consumer.

Further, with the help of machine learning, brands can quickly analyze and process endless numbers of data. This data analysis helps brands determine the best time and day to contact the users. It also helps businesses figure out how frequently should they send out the message, what language will attract the readers the most and the triggers that will make the consumers open and read the mail.

Since with the standard A/B testing, there are several possibilities of error; here AI can help brands curate personalized email content.