January 23, 2018

11 Digital Marketing Buzzwords to Know and Love in 2018

Well, it’s 2018, so now's the time to get your marketing plan in place, if you haven't done so already.
To help, we think you'll need to be aware of these marketing buzzwords in 2018.

Don’t worry, they’re not the useless jargon style buzzwords so many people loathe. These are useful marketing terms that will need to be part of your vocabulary this year.

Here are your digital marketing buzzwords for 2018:

Algorithm – Everyone wants to talk about Google’s algorithm updates or the Facebook algorithm making it hard for businesses to get their marketing messages in front of their target audience, but what does it really mean?

Well, you can think of an algorithm as a formula. It’s a set of rules Google or Facebook uses to determine what content shows up where. So, Google uses its algorithm to determine which businesses and websites show up for certain searches, while Facebook uses its algorithm to determine which posts are most important and relevant to its users.
SEO – SEO stands for search engine optimization and it's the way that we optimize for Google’s algorithm.
SEO involves optimizing your business’s website for searches by adding keywords, meta-tags and other information that search engines need to know in order to rank your business in the right searches for the right consumers. Don’t forget there’s more than one kind of SEO. 
Marketing Automation – Marketing automation is exactly what it sounds like - it's software which enables you to automate certain marketing tasks.
Even if this makes it sound hands off for you, you still need a human touch to set up your automation and make sure everything continues to run smoothly.
AI – AI stands for artificial intelligence, and it’s taking over the marketing world. You can think of AI as any time a machine mimics human intelligence.
Those algorithms we mentioned earlier are one example of how AI impacts your marketing strategies - the algorithms replace humans by quickly figuring out which businesses or websites should show up in your search results, News Feed, etc. AI is also used in advertising to determine which consumers see your business's ads in search results or their Facebook newsfeeds.
AI is already an important part of digital marketing, but we expect it to become even bigger in 2018 and beyond.
Customer Journey – Your consumer’s path to purchase is longer than you think and involves multiple touchpoints across different channels and devices.
People don’t purchase products or services after the first click – it's much more complicated than that. The customer journey is one of the most important things to understand when creating a digital marketing strategy. 
Omnichannel – Along the same lines, omnichannel marketing means creating a seamless online presence (and marketing plan) that reaches customers wherever they’re searching or browsing.
Because the consumer’s path to purchase is longer and more complicated than it used to be, omnichannel marketing is more important than ever.
Attribution – Attribution is a fancy way to say figuring out which marketing channels are driving ROI (ROI was one of our buzzwords for 2017).
Attribution can be tricky, though, since consumers will likely interact with your business in a few different ways (visit your website, scroll through your social media, be served a retargeting ad or any other number of ways) before making a purchase.
You can track attribution through the first way a customer ever interacted with your business, assign attribution to each step of the way or even use the very last action/interaction before the customer made a purchase.
Geofencing – Geofencing is a form of location-based marketing.
It's setting a virtual boundary around a specific location. Think of it like drawing a circle (or polygon) around your business on a map to target people who are in the area.
Businesses that have an app can use geofencing to target people near the business and draw them in with a special offer or promotion.
Micro-Moments – Google talks about micro-moments all the time - they’re those little moments in your life when you need help with something so you reach for your phone.
Micro-moments are broken down into moments such as “I want to know,” “I want to go” and “I want to do,” among others. The point of micro-moments is to understand that there are plenty of small moments when you can be there for a consumer if your business has a consistent, correct online presence.
Smart Content – For a long time, everyone was saying that content is king, but it looks like smart content may be planning to usurp the throne.
Smart content is a term that people are throwing around a lot right now. It refers to personalized content that's designed to meet a consumer’s needs. This could be anything from adding the consumer’s name to an email or personalizing a call-to-action depending on where the consumer is in the buying cycle.
Hyperlocal – The word “hyperlocal” is nothing new, and neither is the marketing concept. But, with Facebook and Google making it easier and easier for local consumers to find the right business in their area, having a hyperlocal marketing strategy is imperative for businesses that want to compete in today’s digital world.
Local search marketing is a good place to get started with a hyperlocal strategy so that your business shows up when local consumers are looking for your products and services.
These are the buzz terms we expect to see a lot of in 2018. Some have been around for a long time, others are new, but it's worth considering what each means in a modern context, and how they relate to your approach. 
Written by: 
Photo by: Alisa Mulder - Unsplash

January 17, 2018

3 Tips For Creating Controversial Marketing Campaigns Without Destroying Your Brand

Is controversy always a good thing for marketing your brand?
It’s that age-old question… is all press good press?
There are supporters on either side of the fence, both armed with examples that suit their purpose.

So which side of the fence are you on?
Let’s reframe the question like this: How much and to what extent is controversy good for marketing, and after what point does it get bad?
The answer is complex, with several things to consider, like:
  1. The level of controversy
  2. The subject of controversy
  3. The connection between the controversy, the conversation and the brand.
This may seem surprising given we are accustomed to seeing high-profile companies running controversial (sometimes highly controversial!) campaigns, and hijacking conversations on social media to rake in the profits that come from increased visibility.
But a study by academics from Wharton Business School found that while “controversy increases the likelihood of discussion at low levels”, beyond a moderate level of controversy, it “actually decreases the likelihood of discussion”.
So what are you meant to do if you want to add the right amount of controversy to your marketing campaign without going too far?
This blog post will explore how to create campaigns that provoke conversations and push the boundaries of social perception without negatively impacting your brand.
Let’s go!

Tip 1: Choose the right controversy

Just as there are different degrees of controversy, there are different types of controversial campaigns that you can undertake:
  1. Shock campaigns
  2. Taboo campaigns
  3. Debatable campaigns
Shock and Taboo campaigns are the ones that provoke widespread commentary on a contentious topic; for example, an ad that trots out the idea that all gamblers are liars or a pro-atheism poster that shows two priests kissing.
Whereas a Debatable campaign is one that has valid and rational points in both its pros and the cons, and is supported by data.
It is highly recommended to opt for a campaign that is Debatable.
That way, you can still stir up a debate, but let people decide where they stand on it. Debatable campaigns don’t solely rely on administering emotional shock or activating trigger points to generate a response, and rarely cause damage to your brand.
With a Debatable campaign, there is a minimal chance of anyone getting offended or hurt, yet everybody participating in the debate becomes aware of your brand. And this additional awareness can be leveraged by you to boost business.
A study conducted by the apartment location start-up Abodo called Tolerance In America’ analyzed 12 million tweets for profane language, then ranked US states on the basis of tolerance.

The headline may be melodramatic, but this type of content is conducive to debate amongst people, as bigotry and intolerance are hot-button topics. Abodo was not adversely affected by putting up this blog post and the campaign was a huge success with more than 620 placements (240 DoFollow links and 280 co-citation links) and more than 67,000 shares which, in turn, stimulated social media discussion.
Another way to successfully harness controversy for your brand is by taking a bold stance on a highly-charged issue.
A great example that springs to mind is Oreo.
So what did Oreo do?
They came out in strong support of gay rights with a Facebook post that contained the image of a multi-colored cookie in the same configuration as the Gay Pride rainbow flag.

The result?
Well, the image sparked fierce debate among the company’s 27 million fans on its Facebook page. While Oreo did cop some flak, the controversy also popularized Oreo wildly and the company reaped a massive dividend from the ensuing publicity.
With more than 50,000 comments and 300,000 likes, it was so successful that there was even a petition for Oreo to manufacture real-life rainbow cookies. The general perception was that Oreo was a ‘brave’ brand for taking a courageous stand on a contentious issue.
There are several other lessons that can be drawn from this example, and some others which we will examine later in the article.
For now, the key takeaways are:
  1. Keep your campaign debatable, or…
  2. Take a stand on a contentious issue and center your campaign around that.

Tip 2: Connect the controversy to your brand

Deciding on a Debatable controversy is not enough. You also have to find a way to connect the controversy to your brand.
Otherwise you will simply be stirring the pot without translating it into measurable outcomes (be it tweets, likes, dislikes, shares, comments or sales profit).
Take this example of a 1-minute video advertisement released by United Nations Women, titled ‘The Autocomplete Truth’, that highlights gender inequality. The campaign compiled the Google autocomplete search results from around the world for the words ‘women should…’
Watch it for yourself.

The campaign was a huge success with the hashtag #womenshould gaining 224 million impressions on Twitter and earning the top spot of ‘Most Shared Ad of 2013’ on Facebook.  The campaign also helped to spark a global debate on gender equality and women’s rights – both offline and online.
You can see how a controversial campaign like this allows the data to speak for itself; in this case, for Google search results from around the world.
Another example of a high-performing controversial campaign is from Sisley.
It subverts the stereotype of fashion models as starving and drug-addled by depicting fashion models ‘snorting’ clothing off a reflective surface.

While debate raged about whether the advertisement was glamorizing drug usage, one thing is for sure, the advertisement was racy and pushed the envelope of good taste. But it did so with a self-referential wink.
While it contained elements of a Shock campaign, it wasn’t just shocking for shock’s sake. And it definitely didn’t do any damage to the brand, with most of its target audience embracing the idea of being ‘fashion junkies’ or ‘addicted’ to expensive style.
Today’s consumers love to take a peek ‘behind the curtain’ and relate to witty content that speaks directly to them, so this type of campaign is well-placed to succeed.

Tip 3: Have a crisis management plan

As we’ve already discussed, controversial marketing campaigns are, by nature, well… controversial.
Before launching your campaign, it is imperative to discuss and have in place a crisis management plan to handle any backlash.
That way, you won’t have to fumble in a conference room putting together a press release in the wake of a social media storm. A good response system is crucial to effective brand management and maintaining your campaign’s integrity.
In other words, have a thoughtful and prepared response ready to go.
Let’s return to the example of the Oreo image.
While the company was successful in gaining massive online and offline support for their post, it did cop some flak.
Despite gaining more followers than they lost (or alienated), Oreo ending up pulling the image from its Facebook page after succumbing to pressure from followers threatening to either boycott or leave the page.
This is exactly the sort of situation you don’t want to wind up in.
Oreo’s panicky response in removing the image made them look less ‘brave’ than initially intended and indicated that their marketing team hadn’t properly considered the potential ramifications of the post. It showed a susceptibility to pressure as well as a regrettable inability to handle criticism.
So, here are some failsafe tips to put a crisis management plan (or as you may prefer to think of it, positive response system) in place.
  1. Take a top-down approach. In other words, people at the top of your organization should take the initiative in responding. This shows that they lead by example and tells the public that their concern is being taken seriously.
  2. Adopt a positive and empathetic tone when engaging with consumer complaints both online and offline. Offer a solution to fix the problem instead of merely apologizing. Show grace, tact and sensitivity.
  3. Follow-through with those affected or offended by the marketing campaign in question to demonstrate an ability to listen to feedback across multiple platforms and action the ensuing results.

In conclusion

Don’t just court controversy for the sake of courting controversy. Instead, ask what it can do for your brand in moderate dosages and examine how it can be connected to your existing marketing messages.
Sometimes it is better to stay cold than to play with fire, however, if you decide to undertake a controversial campaign, use the above tips to generate the positive results you want.
Remember, your aim should never be to offend anybody, simply to tap into popular ideas and debate as an integral part of your engagement strategy.
Author: Vaibhav Kakkar is Co-Founder and Chief Growth Officer at RankWatch and NotifyFox, Software Solutions that help digital marketers perform better. Apart from helping businesses succeed online and writing about Internet Marketing, he spends time digging deep into the beautiful world of search engine algorithms. You can connect with him on LinkedIn

January 12, 2018

What is Deep Learning? Here's Everything Marketers Need to Know

The machines are here.

You may have heard rumors about artificial intelligence (AI) potentially taking over our jobs. And the question is: Should you be concerned?
In my opinion, we should be excited.
AI -- especially “deep learning” technology -- brings new opportunities and innovation in the way digital marketing, sales, and customer support are handled.
But what is deep learning? How does it work? And how can it be applied to marketing and sales in your company?
What Is Deep Learning?
Deep learning is a discipline within AI that uses algorithms mimicking the human brain. Deep learning algorithms use neural networks to learn a certain task. Neural networks consist of interconnected neurons that process data in both the human brain and computers.

Neural Networks in Advertising

Let’s assume we are an online car dealership, and we want to use real-time bidding (RTB) as a mechanism to buy ad space for our product on other websites -- for retargeting purposes.
RTB is an automated process that takes place in a short time frame of under 100 milliseconds. When a user visits a website, an advertiser is alerted, and a series of actions determines whether or not that advertiser bids for an ad display. Have a look at the image below:
Source: Periscopix

In RTB, we use software to decide if we want to bid for a certain ad -- the software will make a decision by predicting how likely the website visitor is to buy one of our products. We call that "buying propensity."
In this instance, we'll use deep learning to make this prediction. That means our RTB software will use a neural network to predict the buying propensity.
The neural network inside our RTB software consists of neurons and the connections between them. The neural network on the above image has only a handful of neurons. In reality, a digital neural network has thousands -- or even millions -- of neurons and connections. 
In this scenario, we want to find out if a certain website visitor is likely to buy a car, and if we should pay for an ad to target her. The result will depend on the interests and actions of the website visitor.
To predict the buying propensity, we first choose several “features” that are key to defining this person’s digital behavior. In our example, those features will consists of which of the following four web pages were visited:
  1. Pricing.
  2. Car Configurator.
  3. Specifications.
  4. Financing.
Those features will influence the output of our neural network -- or, essentially, our conclusion. That output can have one of two values:
  1. The website visitor is interested in the product, or “ready to buy.” Conclusion: We should display an ad.
  2. The website visitor is not interested in the product, or "not ready." Conclusion: Do not show an ad.

How the Neural Network Functions

Let's have a closer look:
For each input, we use “0” or “1”.
“1” means the user has visited the webpage. The neurons in the middle will add the values of their connected neurons using weights -- or, more simply put, they define the importance of each visited webpage.
This process continues from left to right, until we reach the “output” neurons -- “ready to buy” or “not ready,” as per our earlier list.
The higher the value of the output, the higher the probability that this output is the correct one -- or the more accurately the network predicts the user’s behavior.
In this example, a website visitor looked at the Pricing and Car Configurator pages, but she skipped Specifications and Financing. Using the numerical system above, we get a “score” of 0.7, which means that there is a 70% chance this user is “ready to buy” our product.
So, if we look at our original formula, that score indicates the conclusion that we should buy the RTB ad placement.

Training of the Neural Network

Now that we know how a neural network functions, let's have a look at how to make sure our output neurons are calculated correctly, in order to make the right decision.
The challenge is to come up with the correct “weight” factors for all the connections inside the neural network, which is why it needs to be trained.
In this context, “training” means that we feed the neural network data from multiple website visitors -- things like visitor features (which web pages users have visited), as well as indicators of their eventual purchase decisions from us (which are labeled as "yes" or "no").
The neural network processes all these data, adjusting the weights of each neuron until the neural network makes appropriate calculations for each person within the training data. Once that step is done, the weights are fixed, and the neural network can more accurately predict the outcome for new website visitors.

The Future of Deep Learning

Democratization of AI

AI is quickly finding its way into marketing tools that we use every day. Take, for example, the AI-powered Chatbot builder by Motion.ai (part of HubSpot), which allows you to easily create and publish your own chatbot.
Another example is Dialogflow, a platform from Google that lets you build a chatbot for your company or service.
It certainly doesn't stop there. AI can assist with the setup of advertising campaigns, hyper-personalize emails, optimize lead scoring, categorize and escalate customer issues, and actually help you with anything that requires data processing or orchestration.
Deep learning can be applied in any area of digital marketing, provided that you have a sufficient amount of “training” data. The challenge is typically to extract data from your various marketing tools -- that's where data integration platforms like Blendr.io will be crucial in connecting your data silos when you start experimenting with deep learning and AI.

The Future: AI ... That Builds New AI

Google explains that the process of designing neural networks often takes a significant amount of time for development and experimentation, because all of the neural network layers have to be crafted by people. That's why Google invented AutoML: AI that can build new and better AI algorithms.
Imagine what that type of technology can bring to something like marketing automation, for example. The AI will be able to build additional, customized AI algorithms that will learn and automatically optimize nurturing campaigns, for example.
Though deep learning may sound complicated, it's a process that, much of the time, boils down to math. Neural networks “learn” in a manner similar to humans: by viewing many examples, and discovering the commonalities among them.
Once the neural network is trained, it can perform complex tasks and a certain level of reasoning. Deep learning and AI can be integrated into many aspects of digital marketing and sales automation. The machines are not coming -- they are already here.
Originally published January 05 2018, updated January 08 2018

Written by Niko Nelissen

photo by: H Heyerlein - unsplash

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