Proactive Marketing vs Reactive in 2020

Consumer intelligence is what marketing is based on. And with the advancements in technology and software that we have available to us today, marketers have endless data and analytics at their fingertips. But how does a marketer move to proactive marketing from reactive marketing? You’d think it would be easy, with said data and dashboards, but that’s not always the case.

Consumers have endless access to information, shopping, videos, music, and so much more online. And while their data definitely points to specific behaviors that can be predicted, we still have to factor in the fact that they’re human. We all go through different moods, needs, wants, and desires that can’t be predicted from even the most robust dashboard of data.

Something else to factor in is MADD — media-attention-deficit disorder. Consumers have been so inundated by media on screens in the past decade that there is now a term for a shorter attention span online. With the amount of media we all consume on a daily basis, it’s no wonder that MADD exists and is something that marketers need to take into account.

Relevance is still important in digital marketing, but distinctiveness must be demonstrated through media delivery as well as creative messaging. Print used to dominate the landscape, but now that we all have mini-computers on us at all times, we have also learned to demand more from our ads.

Maintaining attention that feeds into a behavioral profile is getting more complex to define and cater to. With the consumer’s ability to pop between YouTube, Facebook, news, email, shopping, dating, and banking, marketers are struggling to define a clear behavior between all those platforms. The overarching behavior seems to be MADD and access to everything at once.

The proactive aspect of marketing is becoming more and more complex, whereas reactive marketing based on something timely or specific behavior-based seems to also have its challenges.

What we already know as marketers are that consumer interests are fickle.

In a statement on the topic from Kevin Virsolvy, Brandwatch senior director international of marketing and demand generation, he stated “Organizations are looking beyond social listening,” he tells MarketingTech. “They need to gather information from a variety of digital sources and combine that with data science and Artificial Intelligence (AI) to bring the voice of the consumer into each and every business-critical decision.

“Brands need to adapt and evolve into digital consumer intelligence,” he adds. “Consumers have more access than ever before to information that brands have little control over. They also know the single most important fact in business: what they want.”

Considering this point, it’s important to note that AI and machine learning in the world of marketing are essential. Bringing the voice of the consumer into each and every business-critical decision is something that many companies do well, and many don’t do at all. Without the right data and application of that data, companies are losing out on making real connections with consumers and delivering value.

It’s easy for a company to assume what their customers want without even asking them themselves. Often, companies completely lose sight of and connection with their customers because the decisions are being made from conversations in the boardroom and not based on hard data and consumer behavior.

And taking into account that consumers both have access to so much online and know exactly what they want, marketers are faced with a gamut of complex options to cater to the varied and evolving needs of the consumer.

What is Proactive Marketing vs Reactive?

In the world of digital marketing, professionals are outfitted with top of the line technology and software that allows them to peer into the mind of the consumer. In reality, both proactive marketing and reactive marketing are useful and necessary.

The collection of data is important in order to learn and solve problems, but there are so many factors that data simply can’t predict. Political and economic factors, special deals and discounts, seasons, pandemics, and so forth.

By basing marketing campaigns solely on past data, our perception and understanding of the present will be hindered, and our interpretation of the future will be limited.

Let’s take a look at the difference between proactive and reactive marketing:

Proactive Marketing:

Proactive marketing is based on data collected over time, and often with the assistance of AI or machine learning. With past data, there are behaviors that can be tracked in order to predict when a person will come online, where they will shop, what they will look for, and how quickly they’ll convert.

Many marketers believe that proactive marketing is more sustainable because of the data, but when there are instant shifts in the market like what we experienced in 2020 with the pandemic, behavior goes out the window.

Data is always going to be a valuable and essential piece of marketing, but we can’t rely on it solely. There are so many factors that feed into a customer making a decision. Relying on data alone will not only be unable to predict behavior during something like an economic downturn, but it’ll also begin to chart erratic behavior as part of the customer’s overall journey. That’s not always going to be the case, but you can’t predict how someone is going to behave online if they’ve just lost their job or fallen ill.

Reactive Marketing:

Reactive marketing is based on real-time and not so much on past data. If your marketing decisions are reflective of what your customers are currently experiencing (a pandemic, for example) you won’t be pulling for a stockpile of behavioral data collected over a long period of time. With reactive marketing, you’re making decisions based on the present that cater to a specific event, emotion, action, or reaction.

With reactive marketing, there is a sense of an upper hand because you’re presenting your product/service as the solution to the problem or situation the customer is currently experiencing. While this solution may only serve temporarily, it’s likely that it could have a larger impact than something based on data collected over time.

Additionally, capitalizing on a need at the moment will only provide a temporary spike in traffic and conversions, but that traffic will more likely be highly interested in the offer.

The Fundamental Difference Between Proactive vs Reactive in Marketing

As you can see, proactive marketing and reactive marketing are fundamentally different. The synthesis of data is on opposite ends of the spectrum. Where proactive marketing makes data-based decisions on historical data and future assumptions, reactive marketing focuses on the evolution and fickle nature of consumer behavior.

The question then becomes: can proactive marketing accurately detect changes in behavior and dynamically react accordingly?

Digital Marketing and Artificial Intelligence

The typical answer to the above question is, no. Proactive marketing is based on past data, simply does not have the capacity to do what AI can do. The human vs machine aspect is surely a factor, but with machine learning, we can quite easily make more informed decisions.

The digital marketing industry has long been an advocate for AI. But more than what many people think AI is, robots and humanoid computers, AI has evolved more into machine learning. Machine learning, as defined by Expert System is as follows:

“Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.”

Surprisingly, this is more common than most consumers even know about. Machine learning can be supervised by engineers, unsupervised entirely, or a combination of the two.

By using machine learning in marketing, this allows for the mass analysis of data and the subsequent application of what was learned to engage the consumer. This is very common with apps to track menstruation, for example. As the user inputs data, the app begins to know them better and make better predictions for ovulation, the start of menstruation, etc. Without the user engaging with the app, there is no machine learning that happens.

Alternatively, a consumer engages with a website, ads, and other platforms that create data that can then be analyzed and behavior predicted, which can be acted upon proactively. Much of this behavior will be linear (predictable) but we also have to factor in unforeseen circumstances and temporary needs (reactive) that can be catered to.

The use of AI and machine learning can make a platform or app more intelligent, and then that data can be used for marketing purposes. But without the user and understanding their own ebbs and flows, marketers are working solely based on historical data and assumptions.

The Linear Marketing Model

The general thought in the marketing industry is that consumer behavior is linear, and therefore highly predictable. There are arguments for both sides of this coin. Yes, the core of most consumers’ behavior is predictable and based on need and can be linear in many ways. However, on the other side of the coin lives the impulses, the environmental effects like the economy, etc, and the fluctuating moods that all humans experience.

When we consider coming at consumer behavior from more than one way, in a nonlinear fashion, there is more room to roll with the punches of life and respond accordingly. Having a baseline of predictability, with room for reaction creates a well-rounded marketing strategy. One with both machine learning and data-driven decisions made by a marketing team.

With human input and rule-setting alongside AI and machine learning, more dynamic marketing strategies can be developed that serve a greater audience. It’s in the tactical executions that many marketers get tunnel vision. By implementing a marketing strategy that has AI at its core, then we’re able to creatively tailor the essence of relevance to consumers.

Behavioral targeting already does this, but adding the AI aspect would take everything that we’re currently doing in the marketing industry to the next level.

Undoubtedly, a world where the two work in harmony is going to have the most traction with the least fall out from wasteful impressions. However, many data analysts prefer to work in the proactive model for analyzing the heaps of data that is collected daily on any consumer. Much of what marketers crave is knowing what to expect, but that simply isn’t how life works.

The linear model of data analysis won’t cut it in 2020 and beyond, which is why a hybrid is what the future holds for us. We need real-time adjustment and creative optimization. This is a both/and scenario, not an either/or that many marketers are trying to implement.

The Bottom Line for Your Business

Evolve or die. AI is becoming a more prominent part of our online space, and that’s something to pay attention to. It’s only going to increase in application and availability, so working with this evolution is absolutely vital.

And again, with a year like 2020, we are going to learn so much about what’s working, what isn’t, and what can use a refresher. It’s easy to stay in a singular, linear model when things like pandemics and global economic hardship aren’t on every headline and in every household.

This year has taught us that nothing can be relied upon solely. We’ve got to have tricks up our sleeve, alternate strategies, and be willing to completely scrap a budget and strategy if that’s not what the market is going to support.

Being flexible and reactive is sometimes a better strategy than being rigid and relying on the way things are typically done. That’s why a hybrid of both proactive and reactive marketing is where the digital marketing industry is headed.

When we evolve, we become more resilient, more intelligent, and more able to adapt. Adaptation to a revolving market with high highs and low lows is more important than all the historical data in the world.

To expand your reach and serve your audience to the best of your ability, get in touch with us at Pico Digital Marketing. We’ll develop custom solutions that will amplify your expertise.

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