In the last two years, there have been important changes in society, modifying patterns of consumption, socialization, work, etc. Given this new normality, data has become, even more so, a key factor for companies to better understand their users and have greater solvency in decision-making.
According to Google, if you search for the term “Big Data” there are 7,750,000,000 search results. It has become one of the most repeated terms since the beginning of the 21st century and has been catapulted by the dotcom revolution when companies began to pay attention to it with quite primitive technology. More than twenty years after the technological leap in this area, the highlight is the change in the purpose of data, which has come to be used in strategic initiatives aligned with the business objectives of companies, guided by the creation of new value and that drive actionability.
When we talk about data there is a triple challenge for all companies to take into account.
- Challenge 1: Get the data right. Big Data is necessary, but not enough, we must combine it with Thick Data and Small Data, to make sure that we are looking for the correct metrics to have a winning offer.
- Challenge 2: Correctly. Once we’ve got the right data, we need to implement the right technology ecosystem to collect it from the right sources, the right methods (privacy compliance), and the right integrations (to avoid enterprise silos).
- Challenge 3: Transform data into action. All the data in the world won’t make a difference unless we turn it into the right information (via visualization) and the right information into the right action (via ideation).
If we think of areas of growth through the use of data, we can refer to many, but one of the fastest growing is that of “marketing campaigns”. We went from massive campaigns where the greatest possible reach was sought to hyper-personalized granular campaigns that are adjusted in real-time with the use of Algorithms, Artificial Intelligence and Machine Learning.
At Designit we have identified some of the most common mistakes that advertisers make in the use of data in marketing campaigns and we propose some useful solutions to avoid making these mistakes.
Error 1: Not correctly defining the public we are targeting. Although it may seem obvious, the starting point is still to clearly and concisely specify who the target audience is.
Solution: We should no longer focus on sociodemographic or age data, the segmentation offered by contextualized, geolocated and well-sanitized data helps us save time, reduce resources, optimize the budget and generate a great return on advertising investment. Advertisers must ‘map’ the journey of their customers (across all channels) from the initial phases of awareness to retention and recommendation, and even unsubscription. Identify the information that is generated through interaction and behavior in order to extract value through it.
If the right audience is confronted at the right time, with the right content, on the right channel, with the right call to action. Then the probability of conversion to the next stage of the journey is maximized.
Mistake 2: Not knowing where our consumers are and how they get around. The data generated by our consumers comes from a multitude of channels, both online and offline.
Solution: If we want to carry out an optimal and personalized marketing campaign, it is essential to know consumption habits, demographic data, socioeconomic level, online and offline interests, the places they visit, the devices they use, among other things.
Mistake 3: High resistance to change. In a very short time we have gone from buying mass media and with guaranteed impressions, to a model of individualized acquisition of advertising inventory using Algorithms, Artificial Intelligence and Machine Learning.
Solution: This process entails a change of mindset, a cultural change and an update of knowledge by the responsible teams in the advertisers to change from a mass mentality to a personalized one. Advertisers must become data-driven companies and use data to make business decisions and create data-driven growth.
Error 4: Not taking into account the optimization of campaigns. Although it seems strange, there are still many advertisers who launch campaigns without optimizing them at any time during the duration of the campaigns.
Solution: We must have several campaign models planned to iterate, it is necessary to carry out multivariate tests, obtain data on the results and evaluate to assess whether an adaptation of creatives, CTAs or ads is necessary to be more effective. Nowadays, these adaptations can be automated so that the performance of the campaigns is optimized in real time, achieving an optimal final return.
Error 5: Lack of clarity when defining campaign KPIs. A very common mistake that many advertisers continue to make is to mix Objectives with KPI’s or key performance indicators.
Solution: For example, if an objective is to Sell Online, the KPI’s can be Number of Unique Visitors to the Online Store, Conversion Rate of an ad, Number of Clicks on the Add to Cart Button, Number of Abandoned Carts, among others. Depending on what the objectives are, we will use the data in one way or another to develop the campaign optimally.
No doubt these mistakes seem very basic and almost impossible to believe, but you would be surprised how many advertisers continue to make them.
The combination of the knowledge and analytical skills of specialized people, along with Algorithms and Artificial Intelligence to ‘create patterns and predict behaviors’ plus the addition of human-centered design to ‘identify emotions, needs, frustrations and motivations’ are the formulas of success to build a data-driven company.
In this way, companies will be able to address their audiences and/or consumers in a more precise and contextualized way, achieving relevance and personalization in messages and creativities for each segment in real time.
Data-driven personalization is no longer an option to evaluate, it is a necessity for brands that want to lead the market in the coming years.