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Guest Times: Big data or sentiment — what is pivotal for a successful digital marketing strategy

Arvind Jain, CEO, NetBiz, writes how brands can make use of both data and sentiment in diverse ways and in tandem as well. The key lies in vigilance, planning, awareness and execution of campaigns

Arvind Jain

The transition from the physical world to that of digital initially raised several questions on the ideal route for marketing a brand. Data, automation, AI and analytics have edged out human intuition, giving way to choices based on factual and statistical reasoning.

Moreover, a non-stop proliferation of computing devices and advancements in technology contributed to the rise in big data. These have revolutionised and added new meaning to the digital realm; evidently giving birth to digital marketing. The market place has been disrupted irrevocably and consumer behaviour has transformed immensely.

One of the critical decisions that flummox marketers is whether to base digital marketing strategies on audience sentiment or data? To understand which of the two can be more effective, it is imperative to begin with how a strategy for a digital marketing campaign is derived.

The tone for a marketing strategy is first set by replicating the brand voice, viz. the attitude and values of a brand that is communicated to the target audience. As each campaign passes, this tone setting becomes more involuntary because the best brands never change their voice; they may tweak it slightly, but very rarely. The objectives and parameters of a campaign are then decided upon, followed by measurability, budget, channels, timelines and action plans, and execution.

Each marketing campaign would have underlying goals like attaining high brand reach and brand engagement among target audiences. For instance, an athleisure apparel brand looking to campaign ‘fitness resolution’ in the New Year would market their brand (scope for both sentiment and data) where their target audience will be bombarded with their content. In other words, they will upload brand videos and photos on social media sites like Instagram or Facebook with relevant hashtags addressing the millennial generation.

There is an abundance of big data on consumer behaviour derived from social media websites, surveys, online reviews, and search engine and web analytics among others. These deep and complex databases are at easy disposal of brands today because AI and analytical tools accumulate and analyse the information to provide insights on consumer profiling, including their interests, demographics, spending habits, preferences etc.

Brands can then use this information in their marketing strategies to ensure optimal brand engagement. For instance, the hypothetical athleisure brand earlier could observe how many individuals have liked, shared, or commented on fitness-related posts on social media sites, and may tweak their fitness campaign according to the relevant data. If target audiences are more into gym workouts then they could focus on gym wear. On the other hand, if audiences are more into adventure sports like hiking or trekking, then they may release a line of clothing suited for such demands and interests.

Sentiment, on the other hand, is a riskier ball game. However, as is the case, higher risks give higher rewards. Sentiment-oriented digital campaigns are common. For instance, Titan has used the sentiment of gifting, that is, a form of celebration during occasions like Diwali (occasions) to great effect while Coca Cola’s ‘share a coke’ campaign (intimacy) was based on the sentiment of human relations where each bottle had a familial relationship like ‘papa’, ‘ma’, ‘didi’, etc. on the labels. Campaigns like these have been immensely successful and have been etched in the memories of consumers. However, it could be argued that a sentiment-oriented campaign could work only with brands that are already well-established.

However, what has been observed is that marketers usually opt for a third route-sentiment analysis. It refers to the cohesion of data analysis and sentiment through algorithms. It is also known as opinion mining because the technological tools analyse the opinions of consumers about a product, service, or brand. In addition, the attitudes and emotions that are expressed on each online comment, feedback, like, dislike and reaction are taken into consideration to understand what consumers mean. However, the technology is fairly one dimensional in the sense that it can understand basic emotion, but not the more complex ones like scepticism, sarcasm, irony, and hope among others. Therefore, it is imperfect but even without the ability to understand contexts it is considered well suited for social media.

In conclusion

While data tracking is easier today because machines are adept at processing vast and deep data, marketers must also focus on sentiment tracking. Digital marketing is an industry that requires awareness of trends, fads, and emotions of consumers in terms of how they respond to the world around them. This will enable brands to make use of certain circumstances; they may either align the sentiments with their products or vice-versa. The market today is entirely about personalisation and engagement. The emotions in humans will always supersede any other factor, and marketers can tap into them through the right channels to attain brand recognition. At the same time, data is a safer bet as it provides a factual understanding of consumer behaviour and provides critical insights. Brands can thus make use of both data and sentiment in diverse ways and in tandem as well. The key, however, lies in vigilance, planning, awareness, and execution of the campaigns.

(Disclaimer: The opinions expressed in this article are those of the author. The facts and opinions appearing in the article do not reflect the views of BestMediaInfo.com and we do not assume any responsibility or liability for the same.)

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