Should advertising investment be higher, lower or better? Appealing to data science may be the key to answering this question.
Striked by the consequences of the coronavirus, marketers have cut their budgets on advertising investment, and only 7% say they are prepared to take advantage of the current situation as an opportunity.
This decline affects even giants like Facebook or Google. As of today, it is estimated that between the two companies they will lose advertising profits equivalent to 44.000 million dollars.
According to the World Federation of Advertisers (WFA), the reduction in advertising investment is a general problem and its consequences vary according to the medium. TV leads the decline with 22%. In turn, online videos have had a decrease of 7%, while investment in display decreased by 14%.
The industry's response is logical given the uncertainty we are experiencing, but it is not necessarily the best decision. In the last century, numerous cases have shown that there are alternatives to hasty cuts.
In the midst of the 1990 recession, McDonald’s decided to cancel its advertising budget, while Pizza Hut and Taco Bell kept it. As a result, both chains saw their revenues grow in double digits, while McDonald’s sales declined dramatically.
Another case is that of Kellogg’s and Post, the two cereal brands that competed for market leadership in the first half of the 20th century. During the Great Depression of 1929, Post cut its advertising investment; Kellogg’s, on the other hand, continued to communicate and emerged from the crisis as the leading brand in its category.
These two examples serve to understand and measure the ways in which one can react to a crisis. However, they are very distant in time. Today the reality that we are going through is different.
Data analysis in business intelligence
During 2019, digital investment in Latin America reached almost 32% of total advertising investment. This added to an immense amount of metrics generated by various online channels; as a result, today brands have many more sources of information. Therefore, they can rely on the data collected to make decisions that optimize their budgets and allow them to keep growing.
If we add up all the payment and social channels, an average campaign processes more than 700 variables. Therefore, analyzing these volumes of information without a tool to centralize and order them is an inefficient task, if not impossible.
We must overcome the next post-pandemic months, it is key to automate and optimize decision-making through the implementation of algorithms and technology at the base of the business.
To do this, data analysis can provide important solutions to marketing departments. Carrying it out will help them discover insights to retain customers; it will optimize the strategies in the search engines; better segment audiences; will automatically adjust the budget and bid allocation; and it will even help determine thresholds for diminishing returns on ad spend.
Through this practice we can find efficiencies that exist today within digital marketing budgets, achieving up to 20% savings without affecting results.
All businesses have information hidden in their data. Information that is hidden in the form of correlations within it and that can help us to solve any kind of problem if it is explored in the appropriate way.
Technology as an ally
Embracing data analytics within organizations is a big change. Applying it means that the company is trained to face technical, human and process challenges. However, this methodology requires gradual operational changes within companies. There should be a transition to reach that goal.
According to the Big Data Executive Survey, 62.5% of those surveyed consider that human resources are the main challenge to transform their organization into data-driven. 7.5% consider technology as a barrier.
Software technology is awesome, but it is not enough to guarantee results alone. For this, human work is necessary and equipping the tool with intelligence that not only helps to process the data more efficiently, but also interprets it and provides recommendations based on the information collected.
By harnessing the power of data science and artificial intelligence, we can make decisions without requiring customers to worry about deploying these capabilities internally. A dynamic that will optimize the strategy in terms of time, costs and results.
For all this, and considering the difficult time we are living in the wake of the coronavirus, the logical question would be: can a communication strategy be improved and investment optimized by implementing data science?
The answer is yes, and here are some helpful practices to achieve that goal.
By using computer vision and performance analysis we can understand and recommend which are the creatives and content that generate the best reception from our audience.
Paid media performance
Through the analysis of means of payment we can understand which investments perform better. This information will allow us to redistribute the budget to optimize strategies and thus obtain better results.
Benchmarks & KPIs
If we have the historical information of our owned and paid media, we can develop intelligent models to define the optimal KPIs for a campaign. Through predictive analysis, we will generate budget recommendations and optimize objectives. This is, in order to improve the performance of the campaigns.
Analysis of online behavior, macro trends by industry, social listening, audience intelligence, projection of objectives and acquisition costs.
In such an uncertain present, the technological bet can be a differential. Both advertisers and agencies must ask themselves if they have enough technology in their strategies. Applying it, after all, can be the quality leap they need to communicate in a more relevant and efficient way.
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