Every once in a while, there's a seismic shift in the industry that changes the way digital advertising is conducted. Sometimes it comes with advanced notice, other times it pops up like an unexpected houseguest that refuses to leave. Either way, it requires a degree of agility from advertisers simply to keep a brand's message vibrant and engaging.
Recent months have left such a shift in the form of unsavory data usage by some of the digital landscape's biggest names. While you, your agency, brand, or campaign were not likely involved in any way, it has changed the way data is now collected, placed a spotlight on data mining techniques, and generally cast a suspicious eye on anyone and anything even tangentially involved.
Advertisers should in no way interpret this as a death knell to the industry as we know it but merely as a mandated shift in processes and procedures that, while inconvenient, isn't the end of the world. While it's true that in this world of big data, advertisers have just begun to see what the potent combination of consumer information and AI-driven insight could lend to a highly personalized ad campaign, recent headlines are a mere detour and nothing more.
The Root of the Problem
Data makes the advertising world go round. It helps brands target a highly segmented audience, analyze and understand their specific affinities, and tailor messages customized to speak to their likes and dislikes, perspectives and foibles. Data and the accompanying ability to craft a personalized message has become the lifeblood of the industry and drives nearly every facet of it in some capacity.
Unfortunately, particular sources of data have been streaming out of platforms in ways that the typical consumer was not only unaware of but also vehemently against. Recent headlines have spoken of data collection practices that went beyond simple social profile mining but, depending on your perspective, possibly intrusive without consumer awareness and underhanded in their intentions.
As a result, congressional hearings commenced, CEOs grilled on network television, and the framework of big data exposed to a shocked and disappointed public. Advertisers, while for the most part not directly implicated, are still very much within the public's bullseye as consumers of those data practices. Just as the industry has done time and time again, however, other doors open where previous ones closed and, with a few slight adjustments, technology can help advertisers get back on the personalized, data-paved road without skipping a beat.
Technology Finds Another Way
Data isn't going to stop driving the industry anytime soon. In fact, while data collection procedures might change, the reliance advertisers have on data will only continue to increase in coming years. So where will the data be coming from now? We're glad you asked because our answer is no different than it would have been before the recent headlines.
The online environment isn't short on opinions. Between likes and dislikes, product and service reviews, catchy celebrity blurbs, and entire platforms devoted to individual perspectives, social influence wields incredible power over the consumer base. In fact, 84% of people now trust online reviews just as much as their friends, and a staggering 91% at least occasionally read them.
Of course, such a reliance on social influence presents an extraordinary opportunity for brands to gauge consumer sentiment levels, and measure shifting tastes in something very near real time. From an advertiser's perspective, the biggest problem with social influence is mainly its size. So many reviews scattered across the digital environment has traditionally made it very difficult for advertisers and brands to draw actionable insight from the mountainous data.
Recent advancements in AI-based marketing platforms have made that job considerably easier by automating the process of sorting through the countless consumer reviews spread throughout the online ecosystem to isolate, interpret, and analyze the most pertinent data.
These platforms can not only find unprompted and unbiased consumer reviews but also reveal nuanced information that provides details otherwise easily missed. Advertisers can use this information to bring new products to market, remarket existing ones, and get an incredibly accurate perspective of their brand identity, strengths, and weaknesses from the consumer's point-of-view.
Although not earth-shattering news, it's important to keep everything in proper context as advertisers search for answers in light of recent news. Heightened scrutiny on responsible data usage in no way impacts the incredible potential held by the combination of big data and algorithmic processing represented in predictive analytics.
Advertisers have never been lacking for data. In fact, they've been sitting on Himalayan-scale heaps of it for decades but have had no way of adequately processing it to draw useful data from its grips. Predictive analytics doesn't require data mined from the hidden shadows of social profiles or digital consumer trails. Instead, it uses historical data – sometimes as detailed as the impact of weather patterns on consumer spending and other highly nuanced factors – to create accurate models that advertisers can use to test their message and tune it to a variety of different affinities.
By using predictive analytics, advertisers can create tailored, personalized marketing campaigns without infringing upon the consumer's digital privacy by using data which has been sitting under their noses all along. Between big data, algorithms, social influence, and other technologically-driven solutions, tightening personal data restrictions don't have to have a negative impact on an advertiser's ability to engage and convert. Remember, a closed offramp on the highway just means you'll take another on your way to the same destination.