For some of us, 2003 doesn’t seem all that long ago. But the year B2E Data Marketing first hung its shingle, the marketing world hadn’t yet moved to a web-centered model. Consumers were still transitioning to using the internet to get information, and digital data was just being recognized as a unique and valuable new source of information.
Every day, your customers are leaving clues about what they might do in the future. Now with help from modern data analytics, there’s no mind reading required to develop savvy marketing strategies built around successful predictions.
As much as businesses wish the buyer’s journey was a straight line from intention to their product, the path today covers varied terrain. The modern, omni-channel buyer’s journey is a blend of interactions that span digital and in-person environments, increasing the need for marketers to have a wider view into customer behaviors and mindset.
More than 85% of Americans now own smartphones, and it’s becoming a primary way to access the internet. In today’s marketing landscape, with its fragmented array of channels, mobile marketing has become a gateway to reach a wide audience, but with targeted precision.
Particularly as Millennials and Gen Z grow in buying power, mobile digital experiences are key to reaching highly-connected customers. Here's what's shaping the mobile marketing landscape in 2023.
Two years ago, a new data term was coined and it’s being called the new secret weapon for businesses.
It’s a big world out there, and the reality is, only a small percentage of people are the right fit for your product or service. That percentage shrinks further when you consider who is actually ready to make a purchase.
Your last digital ad campaign didn’t perform well. Time to scrap the whole thing and start over?
According to a survey by Epsilon, 80% of marketers rely on third-party cookies – the small pieces of data stored in internet browsers to track a user’s online behaviors – in their digital advertising efforts. But as Google’s cookie-less future draws near, it’s important to take action to prepare for the changes.
You may have heard that third-party cookies, which have been marketers’ prime way of tracking online behaviors, are on their way out.
Though the future may not have cookies, it will have Topics.
Google Topics is the proposed privacy-friendly alternative to third-party cookies. Though it’s still early and there are many questions to be answered, wise marketers can begin to familiarize themselves with how the cookie alternative will work. Here’s what we know now.
What is Google Topics and How is it Different than Third-Party Cookies?
To put it (very) simply, Google Topics will change ad targeting from specific to something more broad. It’s an attempt to achieve compromise between competing interests for user privacy and ad personalization.
Topics proposes to create a system that assigns a user a handful of interests according to the websites they have visited recently. These interests determine the content of the ads they are shown.
This is far less granular than the third-party cookie system, which can track the specific websites a user visited. Advertisers had been able to use third-party cookies for highly targeted ad strategies such as retargeting. Retargeting enables marketers to show consumers ads for products they searched for on completely different sites – or, as some describe, when a Google search “follows you around the internet.”
How Will Topics Work?
With Topics, Google will label each website with a high-level topic (for example: sports, autos and vehicles, women’s clothing). The current proposed list has 350 topics to prevent user information from getting too detailed, but Google has said the list could expand to into the thousands. Google has said the list won’t include sensitive categories such as race, religion, sexual orientation, and potential others.
At any given time, a user’s browser will associate itself with up to five topics that reflect browsing behavior within the last three weeks – plus one random topic. Evidently, the random topic is meant to throw off companies that may try to attempt to discern a user’s identity from their topics list.
The topics are shared with advertisers to help them target ads without knowing the specific sites a consumer has visited. But, there will be more control on the user’s end. They will be able to see the topics associated with their browsing behavior and remove any they don’t like, or completely disable them in Chrome’s settings.
How Can Marketers Prepare?
Change has become the norm in the fast-paced world of digital marketing, and the phase-out of third-party cookies is yet another example. Making a successful pivot first will involve moving to a first-party data strategy.
First-party data is the information about your customers you directly collect and own. It can be acquired through a variety of channels, both online and offline, including first-party cookies on your website, an app, social media, your customer service department, or surveys.
So, how much first-party data do you have? If there are gaps, it’s time to amp up your data collection. Remember, this is a long-term strategy – so start now!
Increase direct access to customers by building traffic to your digital channels. Over time, you’ll be able to decipher trends in behavior, engagement, preferences, and topics of interest. You can layer in online forms and surveys to continue expanding your universe of useful data.
As website traffic increases, you might notice that a large percentage of visitors are anonymous – that is, you haven’t yet captured information about them. But, with increased web traffic, it’s possible to leverage additional techniques to profile anonymous web visitors and glean more detailed data that’s incredibly valuable in your marketing efforts.
At the end of the day, Google is the market leader in online advertising, and it is in marketers’ best interest to adapt to its changing model. There’s still much to learn, but being open and flexible to change in the world of digital marketing is always a solid strategy. If you’re considering a refresh for your digital advertising plans, schedule a complementary conversation to learn how we can help.
For decades, opinion-measuring techniques like focus groups and phone surveys were key methods of primary market research. This often meant identifying and recruiting a representative audience sample and engaging professional researchers to facilitate the process. It was expensive and cumbersome, but it was important for enterprises to keep their finger on the pulse of consumer sentiment.
For small and medium-sized businesses, though, conducting regular focus groups and surveys simply wasn’t practical. So, we’ll bet that many SMB marketers will be glad to learn that the primary research of the past is being replaced by new methods of sentiment analysis that are faster, cheaper – and often better.
Does My Business Need Sentiment Analysis?
It’s extremely useful for marketers to understand how current or prospective customers feel about a variety of things, such as the company brand, industry trends, specific products, or relevant issues. These is one area where it may actually be useful for businesses to take cues from politicians, who often use this kind of analysis to gauge public opinion as part of their planning and strategy.
In the business world, sentiment analysis can provide insights into:
- Phrases or emotions that reflect brand reputation.
- How people are talking about your, or a competitor’s brand.
- Whether customer interactions are positive or negative.
- How well a company is serving customers.
- Reactions to certain products or services.
These sentiments can often be correlated directly to a business’ key performance indicators.
Four Key Advantages of Modern Sentiment Analysis
Social media and digital communications have opened the door to entirely new methods of gaining customer insight. Now, artificial intelligence can process language from social media, online reviews, customer service logs, and other data sources to detect patterns in text and classify the emotional tone.
In many ways, these new approaches are proving to have key advantages over previous methods.
It’s more representative. Past methods relied on a small number of people to speak for a larger group. AI-powered sentiment analysis is conducted at scale, with the ability to examine massive troves of opinion data from various sources. It can provide more representative views of a larger population.
It’s more accurate. There’s a significant drawback of conducting research via in-person interviews …
People, unfortunately, don’t tell the truth.
It may sound a bit harsh, and we’re not implying anything malicious or overly devious. It’s simply a natural human tendency to worry about being judged – even by a professional researcher. People often answer questions to reflect how they want to be perceived instead of how they actually behave or feel.
Modern sentiment analysis research is conducted very differently. It analyzes unstructured and spontaneous feedback, where there isn’t the same “performative” aspect. And certainly, people can still be untruthful, but a small group has less opportunity to skew the results.
It’s faster. The availability of online data combined with modern AI tools means brands can get an incredibly quick read on brand sentiment or a specific issue. It’s faster and simpler to conduct regular “temperature checks” and to measure audience sentiments before and after key events, such as a product launch or announcement. It’s even possible to gauge reactions in real-time.
It can monitor shifts. We’re living a dynamic age where information is shared rapidly – and attitudes can change just as quickly. The old methods of sentiment research captured a moment in time. AI and machine learning can monitor continuously, tracking not just snapshots, but how sentiments evolve and change. This puts brands in a position to be more nimble, recalibrating quickly if perceptions move off-course.