Data Science And The Art Of Influencer Marketing
Gone are the days when social media was just about sharing photos, chatting or connecting with long lost school friends. Today, social media has become a go-to platform for brands and businesses seeking effective marketing. For example, Instagram has evolved tremendously over the years. According to Statista, the photo-sharing platform had reached 1 billion monthly active users as of June 2018, up from 800 million in September 2017. And with this skyrocketing popularity of social media, a new industry has been formed — the influencer marketing industry. Today, people don’t rely on traditional advertisements for recommendations, they are looking for recommendations from other people. This downfall of traditional advertisement has pushed the influencer marketing to a higher level. If in case you don’t know who an influencer is, it is an individual who has more than average impact on a specific niche. Influencer market is dawning, and with that, the challenges for brands to carry out a successful influencer marketing is also increasing. And as a solution to that, many think that data science can be a great option. But how data science help discover the relevant influencer? When a brand or a business decides to go with an influencer marketing campaign, the first question that emerges is how to find the most relevant influencer? There are numerous influencers all across the world who has got a tremendous audience, however, there is a clash — is the audience connecting well? are the followers relevant? A Research On The Niche With the help of algorithms, a brand can first figure out what is most discussed topics on social media. This helps them in not only deciding the best platform but also helps in discovering potential influencers that have the most relevant audience pool. Also, by analysing large volumes of interactions on a profile — from the follower base to engagements, one can find out whether an influencer is relevant for the brand to carry out the campaign. Content Filtration This is one of the major tasks that a brand should do before going ahead with influencer marketing. For example, there is a footwear brand (Brand A) who is has a figured out a bunch of great content. However, not all of them are completely relevant. So, in order to find the most relevant content, brands need to filter out useless content. So, in this scenario, data science and ML can help. By using a system that takes a look into all the elements of the content — from the image to comments — Brand A can figure out which are the contents that are not related to footwear. Eliminating the Spammer The internet is flooded with bots, trolls and spammers, and it is one of the major challenges for every brand. So, in order to have a successful marketing campaign, you have to find the real influencers. By using machine learning, a brand can discover the accounts that don’t fulfill the brand’s criteria or that doesn’t interact with its audience. The ML system can go through the comments on the posts and let the brand know whether it’s a bot generated comment or interactive comment done by a human. The Forbes Way Of Using Data According to a 2017 Forbes’ Study, Loyalty card data, Promotional offers etc. can be great ways to witness the impact of an influencer marketing campaign. Let’s have a look at how these factors can make a difference. Loyalty Card Data Simply put, it is a consumer incentive-based card that helps a retailer to record what the consumer is buying and understand his product choices. The major benefit of a loyalty card is it produces a huge number of data which can later be used to figure out whether the same consumer shows interest towards a product when introduced by an influencer. There loyalty card data are considered to be the game changer when it comes to influencer marketing. Promotional Offers This is another way to gather and analyse data when it comes to influencer marketing. Often times, influencer marketing campaigns consist of a code that let the consumer have a discount on a particular product. However, this is not just about driving sales, it also produces a huge bunch of data that can be used to figure out whether people are more interested in buying products recommended by a person or a product advertised in a traditional way. Bottom Line Over the years, data science has transformed several industries significantly. And in terms of influencer marketing, it would definitely do wonder if the data is utilized wisely. When it comes to influencer marketing, it all about content intelligence and audience interaction. And the data that produced on a daily basis will play a vital role in creating strategic insights. Influencer marketing is evolving and with time, it is just going to bigger and better.
Gone are the days when social media was just about sharing photos, chatting or connecting with long lost school friends. Today, social media has become a go-to platform for brands and businesses seeking effective marketing. For example, Instagram has evolved tremendously over the years. According to Statista, the photo-sharing platform had reached 1 billion monthly […]
Influencer marketing is evolving and with time, the data that is produced on a daily basis will play a vital role in creating strategic insights.
["apm data science", "Data Science", "industries transformed by big data", "insights", "Marketing", "social media"]
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["AI", "machine learning", "ML", "data science", "RAG", "R", "Go", "ViT", "programming_languages:R", "programming_languages:Go"]
Harshajit is a writer / blogger / vlogger. A passionate music lover whose talents range from dance to video making to cooking. Football runs in his blood. Like literally!
He is also a self-proclaimed technician and likes repairing and fixing stuff. When he is not writing or making videos, you can find him reading books/blogs or watching videos that motivate him or teaches him new things.