How Tech And Big Data Have Permanently Changed The Marketing Landscape

Technology and data aren’t just fueling today’s marketing, they’re giving it the jump to hyperspace. It’s one of the most dramatic shifts in the marketing landscape since the invention of the smartphone.

Yet, technology’s impact on marketing is roughly equivalent to ten phones being created all at the same time. Mobile app development, social media platforms, big data, self-service analytics tools, cloud computing, sophisticated machine learning and so many other technologies are all happening simultaneously and springboarding off of one another.

Collectively, all of these new tools are opening new doors and allowing marketers to reach, target, and influence a much larger number of potential customers than ever before.

Big Data in Marketing

Of all of the new technologies bulldozing the marketing landscape into something entirely new, big data and analytics tools are arguably causing one of the biggest shifts. In terms of marketing, big data allows professionals to take a lot of the guessing and opinion out of their job.

Marketers have historically created campaigns, messages and other tactics with little evidence to justify the potential cost versus the effectiveness of the strategy. They mostly relied on past experiences and previous campaigns:

“We tried a similar marketing campaign three years ago and it was very effective, so experience tells me that it will be effective again.”

This isn’t a bad assumption, but it is limited by being just that – an assumption. You’re assuming that the market hasn’t changed in three years and that your target audience is still influenced by the same types of campaigns and messages and with the same amount of gusto.

But people change, attitudes change, needs change and they all change very quickly, especially in today’s hyper-connected landscape.

Big data brings precision to marketing. It allows a company to inject math, numbers and evidence into strategies that have historically been subjectively analyzed via only opinion and past experiences.

Big data also empowers marketing teams to better understand what drives their target audiences. This enables them to better measure the impact and effectiveness of their marketing spend. As attitudes change, or new marketing channels are introduced, big data makes it much easier to adapt and adjust to meet those shifts.

Understanding these changes and how big data is altering the marketing landscape is key to surviving the Digital Age. Consider this a road map to the new marketing world.

Marketers Approach Decision Making With A Blend Of Opinion And Data

Big data is not the meteor that blasts the opinion-oriented marketing dinosaurs into extinction. It is, however, causing marketers to evolve and adapt. In the past, I’ve talked before about being “data informed,” rather than “data-driven.”

Data informed calls for both data-born insights and past experiences to be blended together. Unfortunately, plenty of people will miss the mark on this; they’ll see the world-shaping impact of big data and assume that it is the end-all-be-all driver of growth and success.

Not only does this assumption vastly undervalue the experiences, thoughts and opinions of their workforce, but it is also irresponsible. Big data analytics tools are powerful and simply more accurate than the opinions and past experiences of even a seasoned marketer. But, “more accurate” doesn’t guarantee 100% precision.

When companies adopt an entirely data-driven approach, they tend to overestimate the accuracy of their insights. This can lead them to make bad decisions with very high confidence; “How can my data be wrong?” they’ll say. But, when the data is bad, that high confidence in false insights will cause greater catastrophe.

Don’t discount the past experiences of your marketers. The landscape is changing, yes, but they knew what it looked like before and that is a very valuable insight in itself. Big data should be used to enhance your current strategies and allow you to identify new areas of marketing opportunity, with the help of opinions.

Small Businesses Follow Large Businesses In Adopting Big Data, And To Greater Reward

Small businesses have long been forced to follow in the footsteps of larger enterprises when it comes to adopting new marketing tools. And, big data is no different.

That said, smaller businesses have a unique advantage when it comes to big data, which is helping them to catch up to their larger counterparts and ultimately use their data more effectively. That advantage is their size.

Typically, smaller businesses have fewer resources – less cash, smaller staffs, tighter budgets and so on. They also have less data and sources creating that data.

For once, having less is an advantage.

Creating the proper foundation to effectively use data analytics tools and cultivate an organization-wide data culture is very much a walk-before-you-run progression. Larger companies are more susceptible to stumbling as a result of forgetting to learn how to walk, in terms of their big data projects.

Smaller businesses have a big data advantage because they have to smart small. This allows them to scale their data tools/needs more appropriately. Whereas large organizations have to jump into the pool’s deep end, small and medium firms get to ease in slowly and get acclimated with the water.

The data queries of a smaller business are easier and require less resources. They don’t need a sophisticated tool to begin pulling valuable insights from their data. Larger companies, on the other hand, have deeper data pockets, which means they need expensive tools to properly mine and process the data.

The disadvantage of starting off running is it can be difficult, even with a staff of data scientists on hand, to know where to start, what data sets to begin analyzing first and why. More data is more overwhelming, which makes it harder to use effectively, especially in a company’s analytics infancy.

Thus, while it has taken small businesses some time to catch up to the big data world (and many are still in that catch up process), they will ultimately use their data more effectively as larger companies.

Because these companies started small, they will have more time to grow their understanding of how to use data analytics tools to their advantage and will experience far fewer missteps.

Real-Time Data Streams Require Marketers To Be More Agile

Big data happens in real-time and while not every company is going to be able to process and take advantage of data streams as they are occurring, some will. This is going to result in another transformative force to the marketing landscape.

The companies that are capable of leveraging real-time information will be able to target their audiences with marketing messages that fulfill needs the moment those needs are realized. In turn, this is going to influence consumers to expect more relevant results that are valuable to them in that particular moment.

This has spurred on a big conversation in marketing about  “micro-moments.’ Mobile devices and smartphones allow us to shop, search, research and so much more in an instant. We’re always connected and always exploring. These moments of wanting to buy or wanting to know are times when consumers are looking for brands to reach out; it’s when they are most welcoming to your marketing messages and content.

By anticipating and targeting these moments, where customers are looking for products, answers to questions, tickets to an event and so on, marketers can achieve much better conversion rates and other key metrics.

The challenge, however, is two fold. Not only do you need the necessary data and capability to process and analyze that data, but you also need agility. The latter is something that some marketing teams struggle with.

While speed has always been a concern of marketers, real-time data insights require strategies to be adjusted on the fly and campaigns to be crafted and implemented in the shortest amount of time.

Such was the case during the infamous Super Bowl XLVIII power outage, when Oreo quickly took to Twitter and dropped their “You Can Still Dunk in the Dark” tagline. They anticipated that viewers of the game would flock to Twitter during the outage and capitalized on that knowledge by producing a quick, simple message that related. This extremely timely ad won the battle royale of Super Bowl ads that year.

Leveraging micro-moments to the effect that Oreo did means you have to ignore typical marketing processes and think swiftly and creatively from your feet. There’s no time for revision or to get approval from a department head.

You have to shoot from the hip and hope you get the mark.

The potential reward is great, as was the case with Oreo, but there’s a big risk too. With less time for revision and approval, there’s a greater propensity for an incorrect brand voice, errors and other issues that detract from the message and even your overall brand experience.

The agility that big data is requiring of marketers may give smaller businesses another advantage. These companies have fewer obstacles to jump through and their processes are less rigid than a large corporation that has many different interests to preserve.

This means that a small business can create and implement ads and other tactics quickly and with far less risk. Unfortunately, many lack the capability and tools to truly take advantage of real-time data.

Customers Increasingly Expect Personalized Experiences

What makes big data so compelling for marketers is that it allows for deeper learning of specific customers and their unique behaviors and attitudes. Not every customer interacts with your brand the same way, which is why marketers segment their audiences.

Big data makes it possible to create segments with even greater accuracy. This hyper-segmentation allows for brands to deliver personalized experiences to customers, which consistently deliver relevant value to keep those individuals brand-loyal for longer (or more frequently, as we’ll discuss later).

At any touchpoint, when a customer interacts with your brand, there is an opportunity to learn and grow your understanding of what that individual expects from you. The challenge has always been having the means to pull all of those individual experiences into a lexicon of everything you know about the individual customer.

Thanks to big data sources and machine learning tools, brands can learn much more about their customers and how to better serve them.

Instead of approaching Susan simply as a member of the middle-aged female with a moderate-salary segment, you can pull data from your interactions with her to learn greater details and produce a more specific marketing segment.

From mobile app check-ins at stores you can determine which store locations she shops and when. Loyalty program activity can help determine how much she spends and even on what products. And, her use (or non-use) of email, text or mobile coupons expresses which types of deals she finds most valuable and through which channels.

All of this information can allow you to produce an experience for Susan that is uniquely her own and fits her specific needs from your brand-customer relationship.

The challenge of gathering data at each interaction and producing a personalized experience for a customer is to know when to stop. The news is littered with stories of data leaks and personal information being stolen. We’re naturally skeptical and wary of our data being collected. Too much personalization is creepy.

Marketers have to remember to preserve each customer’s sense of security, while simultaneously using their non-identifying information to improve strategies and message targeting.

Marketing Is No Longer About Mass Communication, But Communicating With The Masses Through A Mass of Channels

Traditionally, marketing was most effectively achieved by using mass communication channels. You wanted your messages to reach as many people as possible, so you turned to television, radio, print etc. to get the word out. While those channels remain extremely valuable today, the Digital Age has created so many newer channels that these mass communicators are no longer a catch all net.

With people utilizing social media channels, IoT, mobile devices and the like, mass communicators aren’t as effective because there are fewer people present on those channels. It’s no longer reaching the masses. Through the utilization of big data, companies can better understand where their target audiences are gathering and when.

This is creating a big shift in the fundamental ways that marketers reach and engage their audiences. Rather than using one or two large, mass communication channels, companies are communicating through many different channels all at once.

Part of this trend is supported by the consumer desire for greater personalization. By reaching out to customers on their favorite channels, at the time they are most likely using it, you help deliver a personal experience that is catered to that individual (and greatly increases your chance of the message actually reaching that customer). Depending on the channel, you can also decrease the likelihood that a customer gets a message that is not relevant to them.

Successfully marketing across all of these different channels has a lot of challenges. First, each channel has its own set of guidelines that influence how your message should be encapsulated (a Tweet has different rules than a Facebook post or an email newsletter). Second, once you’ve created different messages for each relevant channel, you have to be concerned about over saturation. If someone is connected to your brand through multiple different touch points, these messages can quickly feel spammy, even if each one is slightly different.

Omnichannel communication requires you to constantly be using your company’s data to evaluate the effectiveness of every message and campaign across all channels. These insights will help you better craft messages that are optimized for individual channels and help protect you (and your target audience) from repetitive content.

As brands continue to get more competent at multi-channel communication, the competition on these mediums is going to heat up and brands will have to develop new ways to engage customers in order to stand out.

Hyper-Loyal Customers Are Headed For Extinction

Maybe not extinction, but the hyper-loyal customer of yesterday is becoming a rarer breed. While personalized brand experiences may be the key to keeping this species alive, micro-moments are giving way to more fickle customers making one-off purchases.

What’s important to realize is that your inability to attract hyper-loyal customers is not a reflection on poor marketing, but rather a shift in the frequency in which today’s customers are willing to switch brands.

When we discussed consumers expectation of personalized experiences, I alluded to the idea that brand loyalty isn’t a matter of keeping customers loyal longer, but attracting their loyalty more frequently. With all the exposure to brands that we face today, loyalty tends to ping pong from company to company, deal to deal. We’re forever chasing the next new experience.

Customer defection is inevitable, but only temporarily, as long as you’re capable of re-engaging them.

To encourage maximum loyalty, marketers have to look at not only leveraging their own data, but also the available data of competitors. For example, analyzing a competing brand’s social media data might yield insights into how you can improve upon certain strategies, capitalize on their shortcomings and ultimately create a more attractive experience than theirs. This entices both new to join and old customers to return.

In other words, fostering customer loyalty today isn’t just about keeping current audiences engaged and enjoying your brand experience longer; it’s also a matter of limiting how much loyalty they award your competitors. This creates a much more competitive marketplace where brands are constantly vying to outdo one another by offering a better experience.


Big data’s effect on the marketing landscape can be summed up in four words: speed, relevance, accuracy and value: Today’s marketing happens fast and is achieved by delivering timely experiences and interactions that are relevant to the individual customer’s needs and provides them with value.

These have always been goals of marketing, but the accuracy that big data provides and the ability to actively learn about customers in real-time creates a world where brand experiences are personalized for each unique customer and there are far fewer irrelevant or non-valuable messages reaching consumers.

Big data is, and will continue to be, a transformative wrecking ball on the marketing and sales world. It’s knocking down trees, leveling out mountains and constructing a superhighway between brand and customer.

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