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Month: July 2017

Who’s Afraid of $5 Branding? – The Future of the Creative Industry in the Age of Automation

Who’s Afraid of $5 Branding? – The Future of the Creative Industry in the Age of Automation

Those of us in the branding industry have seen several emerging trends that appear destined to integrate permanently into the way we do business. These trends are as far-reaching and diverse as businesses embracing purposeful brand activism, to the ever-growing rise of artificial intelligence in branding strategy and execution.

Friend or Foe? Artificial Intelligence and Branding

New developments in AI, such as automation and machine learning, have already creeped into the world of brand strategy and design. Through a quick analysis of user preferences and tastes, people are using AI to analyze a user’s design style and suggest appropriate fonts and logos. It’s not hard to see the appeal: automated branding takes minutes rather than days, and costs a fraction of what a human designer would charge.

Some now fear the next stage–that using machines to design and implement branding will put human designers out of work. This sort of debate isn’t new. But, despite similar protests in the past, today all sorts of automated services, from self-checkout counters at grocery stores to electronic toll booths, are commonplace.

Conversations as well as services are becoming increasingly automated; even Facebook has introduced bots that can book you a car and order you food, and Amazon’s popular Echo can automate basic tasks in your home. Given this trend, should designers be worried?

Not really. While concern in the business world may have some merit, the use of artificial intelligence for branding is decidedly different from typical examples of machine labor. While it’s true that self-checkout counters might eventually replace human cashiers, automated branding does not replace designers, nor is it likely to. Instead, automated branding opens up doors for startups and small businesses that otherwise wouldn’t have the budget for good design. And as automated branding fills this niche, designers–who could incorporate AI into their own design strategy–could benefit.

The Democratization of Branding

Well-designed branding should not be the exclusive domain of the biggest and most successful companies. Both the gig economy and the automated creative industry are now providing opportunities for small players to get a leg up in their respective fields. As is the case with hiring freelancers from sites like Task Rabbit and others, automated design providers allow humble businesses to enjoy quality work with limited budgets. Considering the kinds of expenses new businesses face, anything that helps them achieve financial independence is a good thing.

And startups aren’t the only businesses that will benefit. Automated branding companies like Tailor Brands service everyone from soccer moms making logos for team uniforms to kids who create branding for gaming clubs. They also service freelancers, dog walkers, and people pursuing their dreams after work. Sure, machine-created logos are used for traditional marketing purposes. But, they’re also amping-up your neighbor’s hobby baking business or social media profile. It’s likely these are things that users wouldn’t have hired a professional designer to do anyway.

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Small E-com, Wanna Know Why You’re Failing?

Small E-com, Wanna Know Why You’re Failing?

The Predictive Analytics Boom and Its Impact on E-commerce Marketers Today

Steadily but surely, predictive analytics has been gaining in popularity. It’s expected to explode this year as it becomes more accessible and goes from being a competitive advantage to a necessity. To fully understand how it impacts e-commerce marketers today, first we’ve got to look back to the past.

Traditionally, predictive analytics has been reserved for top brands such as eBay and Netflix. eBay is focused on using predictive analytics to make its shopping experience better for both buyers and sellers. Indeed, eBay considered predictive analytics so important that it acquired SalesPredict to boost its AI, machine learning and data science efforts.

When a company like eBay spends millions on an acquisition for the sake of predictive analytics, e-commerce marketers must take note.

There are a couple of reasons that eBay made this move:

  • Better understanding of what their customers wanted.
  • Access to advanced insights for improving conversion rates and accelerating sales cycles.
  • More targeted offers with relevant information for buyers.
  • The ability to build-out predictive models that can define the probability of selling a given product at a given price over time.

In other words, predictive analytics answers some of the biggest challenges facing e-commerce marketers and business owners.

How to Use Predictive Analytics Like eBay Does

To achieve similar benefits to eBay, you only need to take the following four steps:

  • Track e-commerce metrics and create a one-day forecast. Then identify any deviation between the forecast and the actual metrics.
  • Determine the cause of deviations from your one-day predictions. Assuming the deviation can be minimized, take steps to do so; otherwise, use it to establish a confidence level in your predictions.
  • Create progressively longer-term predictions, ranging from one day to 18 months.
  • Use predictions to answer “what if” questions such as, “What if we increase advertising spend?” or “what if we decrease stock for this item?” and more.

Obviously, it’s easier said than done, but with the proper tools and strategy, you can be predicting the future in no time.

Overcoming Common Challenges

Predictive analytics isn’t without its challenges. For one, it can be difficult to trust the data, especially when your “gut” and past experiences may indicate otherwise. But even more challenging is doing predictive analytics right.

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