by Fronetics | Jun 19, 2019 | Blog, Content Marketing, Current Events, Logistics, Marketing, Supply Chain
As the internet is increasingly dominated by visual content, social media analytics are failing to keep up.
Highlights:
- Most social media analytics tools are purely text-based.
- Even tools that analyze images are costly and offer limited insights.
- We predict that machine learning capabilities will improve and the gap between analytics capability and brands’ needs will close.
Here’s an interesting conundrum: social media, and the web at large, is becoming increasingly visual, and social media marketing relies on increasingly sophisticated analytics. However, most of the analytics tools out there are woefully unable to make sense of the visual content that is dominating social media. The alarming truth is that social media analytics are failing to capture invaluable data on visual content.
How social media analytics are failing to keep up
Big data and artificial intelligence expert Kalev Leetaru describes the shortfalls of social media analytics by detailing what they can — and can’t — do. While the capabilities of visual analytics have grown in the past several years, as Leetaru points out, most analytics tools that claim to analyze visual images are in fact based on textual or structural aspects of the image, not the visual content itself.
“The overwhelming majority of production social media analytics research relies primarily on hashtags and associated caption text, rather than the actual contents of the images themselves,” writes Leetaru. Instead, “from simplistic bag of words counting algorithms through advanced deep learning approaches, it is text that forms the lens through which we see social media.”
It’s important to note that this text-based approach is true not only for social media analytics, but for search engine algorithms. At Fronetics, we are constantly advising our clients to make use of visual content, from images to infographics to video, in their digital marketing efforts. But we always advise that marketers optimize their images for search engines, both by tagging all visual assets and publishing transcripts to go along with video or infographics.
[bctt tweet=”We always advise that marketers optimize their images for search engines, both by tagging all visual assets and publishing transcripts to go along with video or infographics.” username=”Fronetics”]
In essence, we’re advising our clients to take advantage of the increasingly visual nature of the internet, while also hedging against the ways in which algorithms and social media analytics are failing to assess visual content. As Leetaru points out, even in the rare cases when an analytics tool offers image analysis, it “typically offers only a few basic lenses through which to analyze that content, such as logos and a small number of topics.”
Of course, analyzing visual content is no easy task, and it’s also not cheap. “Images don’t capture reality, they construct it,” observes Leetaru. Not only are there all kinds of variables, like framing or lighting, that come into play, but there is a tremendous amount of non-visual context that determines how an image will be received. And the fact is that “current deep learning approaches are largely unable to incorporate such external world knowledge into their assessments.”
The problem with analytical failure
It’s important for marketers to recognize that, at the current moment, there is a gap between the capabilities of analytics tools and the analytics needs for modern digital marketing. As we as a society “increasingly express ourselves exclusively through visual forms,” brands desperately need insights about this visual expression.
Leetaru sums up the problem with sobering simplicity: “As social media becomes more visual, it becomes less accessible to our data-mining algorithms. In turn, as social media is less and less data minable, we are less and less able to understand it.”
Perhaps even more alarmingly, he cautions that “given that visual expression skews towards the younger and influencer demographics of greatest interest to many brands, this transition is especially damaging to their ability to extract useful insights from social media.”
Essentially, what Leetaru is recognizing is that we’re at a perilous moment for digital marketing. Just when the possibilities for content creation and dissemination seem endless, social media analytics are failing to offer up the insights needed to shape these processes in an increasingly visual climate.
“In the end, as social platforms rush towards a visual-first world, the vast landscape of social analytics is getting less and less representative of what we’re really talking about,” concludes Leetaru.
What does the future hold for analyzing visual data?
While you may be thinking that the future looks pretty bleak in light of how social media analytics are failing us, there’s a silver lining. If there’s one constant when it comes to social media marketing, it’s that when there’s a demand, sooner or later, supply will catch up.
It’s true that the current visual analytics capabilities of most platforms are far behind what’s needed. But at Fronetics, we predict that deep machine-learning capacities will start to catch up, and increasingly sophisticated analytical capabilities will become available to a wider segment of the market.
Currently, social media analytics can recognize text, faces, and brand logos within images. While these capabilities are, at present, too costly for most companies to take advantage of, we’re keeping our eye on some emerging technologies. For example, analytics provider Scraawl has recently released a tool called Scraawl PixL, which will allow users to run object and face detection, as well as Optimal Character Recognition, which extracts text from images.
Expect to see more tools like PixL on the market, offering increasing sophistication. While social media analytics are failing to keep up with the onslaught of visual data at the moment, we predict that they won’t be behind for long.
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by Jennifer Hart Yim | Jan 30, 2019 | Blog, Content Marketing, Current Events, Logistics, Marketing, Supply Chain, Talent
Supply Chain skills have never been in more demand and the work has never been more interesting. Here’s a look at the best degree for supply chain management.
Highlights:
- Today’s supply chain professionals need to be well-versed in data analysis, presentation skills, negotiation skills, project management skills.
- Individual career objectives and educational options can help determine the best degree.
This guest post comes to us from Argentus Supply Chain Recruiting, a boutique recruitment firm specializing in Supply Chain Management and Procurement.
Supply Chain Management was seen as a back-office profession. People tended to rise from shop floors and warehouses into management roles and eventually – for the most high-performing individuals – Senior Director and C-Suite positions. It’s always been one of those fields that people “fall into.” Once they found themselves in a Supply Chain or Procurement job, people tended to look around and see how important it was to the business. They’d experience the fast pace, see the immense ten-dimensional puzzle involved in getting a product to market, the global scope, and be hooked.
It used to be a truism that no teenager decides that they want to get into Supply Chain, even those who had their sights set on the corporate world and not other paths like medicine or law. Supply Chain used to be the kid brother to other, more “glamorous” corporate functions like marketing and finance: misunderstood, transactional, and frankly thankless work.
No longer.
In 2018, Supply Chain Management is a key market differentiator for companies in industries as diverse as consumer goods, retail, pharmaceutical, manufacturing, you name it. Supply Chain skills have never been in more demand in the corporate word, and the work has never been more interesting. Many of the top companies in the world are waging a constant war for Supply Chain talent, with baby boomers retiring and strong economic growth driving demand. Young people are starting to wake up to the huge amount of opportunity in the field.
[bctt tweet=”Today’s Supply Chain professionals need to be well-versed in data analysis, presentation skills, negotiation skills, project management skills, as well as the know-it-when-you-see it overall skill of “business acumen.”” username=”Fronetics”]
At the same time, companies are increasing educational requirements, which makes sense: today’s Supply Chain professionals need to be well-versed in data analysis, presentation skills, negotiation skills, project management skills, as well as the know-it-when-you-see it overall skill of “business acumen.” In our recruitment practice, we’re noticing that more clients are requiring a university degree as a hard-and-fast requirement for jobs.
The requirement often ends there. “A degree.” Which means that there are lots of educational avenues aspiring Supply Chain professionals can take to set themselves apart from the competition. But it can be daunting: should you do an Engineering degree with a focus on Industrial Engineering? Should you do a business degree? A liberal arts degree and then an MBA? Or should you forgo a formal degree and pursue certifications like CSCMP and APICS from industry associations?
It depends. It’s hard to arrive at a definitive answer. Why is that?
- Individual career objectives vary. For example, someone who wants to pursue a career in sourcing and Procurement will probably be better served by a business degree than an engineering degree. And someone who’s interested in Production Planning, Supply Planning, and/or Demand Planning is probably best served by a STEM degree that features a lot of quantitative analysis.
- Educational options vary. More schools are offering Supply Chain specialties as part of MBA programs, as well as at the undergrad and college levels. More traditional programs (engineering, business, etc.) are taking steps to prepare students for careers in Supply Chain Management. But options for programs vary based on geography and the grades that any one candidate brings to the table.
That said, we still think it’s worthwhile to give some tips for people exploring their education options in the field. So we put the question to our network of established Supply Chain professionals to see what they had to say.
Here are some of the more insightful responses:
“Engineering degree with focus in database structures and statistics can equip one with the required skills for this domain. Presently all SCM jobs require one to be able to work with ERP systems so it is nice to have understanding about the underlying concepts.”
“The easiest that i can think of is Industrial Engineering which is a mix of Engineering/Mgt/commercial/statistics subjects. My degree in IE was a sound base to launch me into a SC/Logistics career. Then top it off with a certification after gaining some work experience. Certifications without some work exposure may turn to be useless. Certifications should be a source of validation of what you know in the discipline. I do hear there are schools/community colleges these days offering SC/Logistics as a degree. In all, any course that exposes and builds a person’s critical thinking skills is ok to get into supply chain.”
“Best degree would be to start working in a warehouse. Try some scheduling work also if you can. For all the value that a degree gives you, nothing beats knowing how goods flow and how truck drivers get stuff from point A to B. Do this for a year, then worry about which degree to get.”
“1) Chemical/Industrial/Mechanical Engineering 2) Economics 3) Business/Commerce with a major in finance 4) a solid liberal arts education from a university that will propel you into a top business school.”
“Engineering or Business provide a great foundation for logical, innovative and strategic thinking.”
Hopefully the above comments can help offer some guidance to anyone who’s interested in embarking on Supply Chain Management as a career path. There are lots of paths to go down. But whether you choose the university, college or certifications route, it’s pretty undeniable that more education is never a bad thing.
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by Fronetics | Nov 13, 2018 | Blog, Content Marketing, Data/Analytics, Logistics, Marketing, Strategy, Supply Chain
The results are in: Artificial intelligence (AI) has significant value for many business sectors. But what are the most effective ways to apply AI to your supply chain management company?
Executives of many leading companies are looking for ways to integrate AI into their operations. A recent McKinsey & Co. study estimates that 40% of the potential value associated with data analytics today comes from techniques called “deep learning.” Deep learning refers to AI that can monitor a system and make adjustments rather than simply repeate a single task. Industry use of deep learning techniques remains relatively low as companies determine how best to use AI to meet business needs.
[bctt tweet=”Using AI this way can improve forecasting accuracy by 10-20%, allowing companies to reduce inventory costs by as much as 5% and generate 2-3% increased revenue.” username=”Fronetics”]
Supply chain management is one of the business sectors that can get the most value out of deep learning techniques. Brick-and-mortar retailers tend to see a 1-2% increase in sales revenue when they use AI to personalize promotions based on customer data analytics. Supply chain management organizations can expect to see greater benefit from AI that forecasts demand by analyzing the underlying market factors. Using AI this way can improve forecasting accuracy by 10-20%, allowing companies to reduce inventory costs by as much as 5% and generate 2-3% increased revenue.
In addition to reducing inventory costs in supply chain management organizations, deep learning can create trillions of dollars in value in marketing and sales revenue and save costs through predictive maintenance. The best way to determine how AI can serve your needs is to look at how your organization uses traditional analytics techniques: AI can often provide higher performance in conducting analytics and introduce additional layers of analysis. The technology is always improving, so the potential value for companies adopting deep learning techniques is expected to continue to rise.
There are, however, obstacles facing companies looking for ways to use AI techniques. It is essential to plan for the security and privacy issues of data analytics. Deep learning works best with large-scale datasets, which not all organizations can assemble or access. The level of expertise necessary to implement and service AI technology comes with added expenses, but determining the right way to apply AI to your organization makes these costs and challenges a rewarding investment.
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by Fronetics | Oct 29, 2018 | Blog, Content Marketing, Logistics, Marketing, Strategy, Supply Chain
What’s more important: prioritizing conversions or building traffic? The simple answer is both. Here’s why you need to balance your efforts for the best results.
The argument for building traffic or optimizing for conversions has no end. Like we stated in our earlier post, it’s a chicken-and-egg style debate. If you don’t optimize for conversions, what is the point of directing traffic to your site? On the flip side, if you don’t build traffic, who is visiting (and converting) on your site?
The problem is countless variables affect which of these goals you prioritize and when. Determining what you should be investing more energy into is dependent on your business, your strategy, and your target audience. Make sure you’re considering all factors when determining what makes the most sense for your brand and its online presence.
Why focus on conversions?
There are three main arguments for prioritizing conversion optimization:
- Low investment, high yield: The return on investment is significant, especially given the low cost of entry and easy process.
- Traffic optimization: while you may not increase traffic, by focusing on conversions you can increase the value of visitors to your website.
- Reinvestment potential: conversions will help generate funds to reinvest in your marketing effort.
All of these arguments focus on quality over quantity. By prioritizing conversions, every visitor becomes more valuable. Even with lower numbers of visitors to your website, if your conversion rates are high, you still realize a substantial return on your investment. The low cost of conversion optimization also makes it easy to implement without breaking the bank. We’ve even done some of the work for you, giving you tips when creating your landing pages.
Why focus on building traffic?
If you aren’t getting visitors to your website, there’s no point in worrying about conversions, right? But that’s not the only reason building traffic should be a priority. A few benefits of focusing on traffic include:
- Brand recognition: visitors will become familiar with your brand and content
- Momentum: concentrating on traffic is a long-term strategy and committing to the long-term gives your marketing efforts time to build momentum.
- Optimizing for value: there are a lot of metrics affiliated with building traffic, this allows you to collect and analyze data to see how you’re doing and to constantly improve.
By increasing traffic to your website and familiarizing new audiences with your brand, you have more opportunities to generate leads and those leads can turn into sales.
Why balance is the answer
[bctt tweet=”The most important thing to remember is that your content marketing strategy is a work in progress that is continually being tweaked. You’ll need to spend time and money prioritizing both building traffic and optimizing for conversions. ” username=”Fronetics”]
The most important thing to remember is that your content marketing strategy is a work in progress that is continually being tweaked. You’ll need to spend time and money prioritizing both building traffic and optimizing for conversions. Here’s Jennifer Hart Yim, Director of Strategy at Fronetics, to explain why we think you need to focus on both to maximize your efforts.
Video: Focus on Conversions or Building Traffic First?
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