We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
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The Future of Customer Experience
Since we’re living in an age where retail chains go bust by the score, the need for an optimal client experience is clearer than ever before. Modern technology offers many opportunities to enrich the experience even further, particularly since it’s developing at breakneck speed. What will client experience look like in, say, 4 years from now? Digital assistants everywhere, but the human touch retains its value – Siri and Cortana are samples of the digital assistants we know now: nice little smartphone tools that amuse us with hilarious conversations and the occasional surprising answer.
Nevertheless, digital assistants may have evolved considerably in the future. They’ll offer truly useful conversations and will assist us in making the right choices. Some web shops are experimenting with chatbots and wizards who try to offer real advice. By 2020, these systems may have matured and offer real and useful advice based on targeted open and closed questioning. They’ll also become a staple in mortar and brick shops. One good example of where we’re heading is Robot Pepper. This physical robot is able to initiate a conversation and assuming it’s designed to do so assist you in purchasing products suitable to your needs.
However their role will change. Robots will look after basic client care, while humans will remain indispensable for more advanced forms of advice that need a human touch. There are various samples of organizations that have subjected an excessively large part of their client care services to automation. In addition, well functioning self service facilities will become more important and will be indispensable by 2020. Including self service portals or active user communities where clients can ask their questions. Interactive shops increase shopping districts attractiveness – In 2020, mortar and brick stores will need to think even more about their relevance.
The great news is that technology offers countless opportunities to give a huge boost to the shopping experience. The only hurdle here’s creativity. That’s a good thing, because shopping should be sexy. Lets take for instance a sneaker store. The moment a client passes the store, he’ll get a personalized deal offer on his smartphone. The latest addition to his favored line of sneakers is available with 20 percent off, and in stock at this store. Once inside, he’ll explain to the digital assistant that he’s searching for a sneaker appropriate for a novice runner. When fitting the sneaker, beamers project walking exercises on the shop floor to test out some of its features. Lastly, the mirror can show him how different colours along with other varieties would look on him using augmented reality. Hyper individualization brings product and shopping experience closer to the consumer – Stores and brands will increasingly collect client data in 2020.
Savvy online marketers know the power of Twitter traffic. Perhaps more than any other social media platform, twitter excels at sending users out from its biosphere, as the short format encourages posting links rather than details. Because of this, if you build a healthy number of followers, you can drive traffic to a destination site almost on demand.
However, that’s only half of the story. If your tweets engage your followers enough to promt a retweet, you can quickly reach an extended audience with viral speed. Naturally, this is an effect that any marketers would like to harness.
So how can you use Twitter most effectively to build followers, retweets and lucrative traffic?
Every business (whether online or off) brags that superior customer service is a top priority; unfortunately, many customers would disagree. In business, the customer gets the last word and their word counts – in sales and profits.
One of the biggest myts in business is that customer service is meeting the needs of their customers or that business is hitting the bull’s eye in superior service. Surveys time and time again reveal that customers are deeply dissatisfied when it comes to customer service and that many business have not earned their loyalty.
Today’s customer is consumer-educated, informed and savvy and for some, price is not always a determinant. But, customer service is always in demand.To differentiate one’s business from another let’s meet the rising expectations of a demanding customer – let’s meet their needs and earn the sale and their loyalty.
How does business differentiate itself from the others in offering superior customer service?
It’s simple: profile your typical customer and understnd them. Then anticipate and meet their needs. It’s not rocket science – it’s just common sense.
Describe your typical customer. Put it on paper. Sometimes it helps to visualize one person, instead of a whole group of customers. Now imagine this person visiting your website, or store. Does that person spend time reading info and details? Does that person shop in certain aisles? Do they like assistant? Do they eventually buy, or not? Does tha person ask questions? What kind of questions? Does that shopper need instructions or how to’s?
How much is your average sale? How often does that customer return? Do you know what links brought that customer to your web site? Do you know what pages the customer is not visiting?
What time of the day does the customer shop?…..
Musica ed intelligenza artificiale
Musical AI – Musica ed intelligenza artificiale
Anche la musica può essere generata dall’intelligenza artificiale grazie all’utilizzo dei dati …allo stesso modo in cui un musicista usa la sua esperienza maturata nel corso dei suoi studi ma il livello di creatività che possono raggiungere le macchine in queste cose è meno complesso, almeno per ora.
Di seguito tre esempi di brani editi da Jukedeck, una start up che produce e commercializza musiche generate interamente da computer.
You can’t stop the wind with your hand…but you can surf it!
The Future Of Sales : Artificial Intelligence (AI ) IN DIGITAL MARKETING
Artificial intelligence (AI) is here to stay and is rapidly becoming part of your everyday life. For example, you can find AI in cellphones, websites, televisions, and cars. So from a marketing perspective, it’s time to ask: “How can I sell more with AI?”
Purpose
First, it’s important to know the purpose of AI. This can be summed up as follows:
The last point is what interests us here. But how, in practical terms, can AI achieve this for you?
Leads
AI can use a vast amount of data to propose sales solutions, products, and potential customers. In other words, AI can identify your most promising leads and what they need. Such a process saves you time. It also enables you to focus your marketing efforts with greater success.
Personal and Accurate
To be more specific: AI can provide you with data about customers that is personal and accurate. You then use it to sell your products and services.
Take almost any major sales website. When you visit, the site makes personalized suggestions for purchases, based on your prior purchase data. This is an example of AI at work.
Website
If you use AI for online sales, you can:
Emails
AI can also improve email sales campaigns.
By analyzing data, AI can help you send custom messages to specific consumer segments. In this way, you target your sales campaign more effectively.
AI Sales Assistants
You may well have experienced AI sales assistants, or chatbots. They appear on a website, engaging a customer in conversation, answering questions, and providing help. This process, in turn, improves your potential to sell.
Your Brand
Your brand is important to you and your customers. Your customers need to respect and trust it.
When you use AI to give your customers individual suggestions and help, their respect and trust in you grows. For example, they know that you are not targeting them with emails and ads randomly and thoughtlessly. Thus, AI can become an integral part of your brand development.
Competitors and Technology
It’s clear that AI can give you a marketing edge. But you need to stay abreast of the technology- it is developing fast. As it does so, cost-effective AI for different business solutions is becoming available. Ensure that you know what’s out there and what you can expect.
Analysis and Strategy
AI is an analytical tool. What’s more, it’s better than humans. And since sales analysis is a critical part of any marketing strategy, AI helps you to identify your opportunities.
Just as important, AI can provide data about your strengths and weaknesses. It enables you to improve sales and reduce wasted time and effort. So why not take a look at what others are doing with AI? Then think about the benefits that it can bring to your business.
Posted by tombennet
When it comes to direct traffic in Analytics, there are two deeply entrenched misconceptions.
The first is that it’s caused almost exclusively by users typing an address into their browser (or clicking on a bookmark). The second is that it’s a Bad Thing, not because it has any overt negative impact on your site’s performance, but rather because it’s somehow immune to further analysis. The prevailing attitude amongst digital marketers is that direct traffic is an unavoidable inconvenience; as a result, discussion of direct is typically limited to ways of attributing it to other channels, or side-stepping the issues associated with it.
In this article, we’ll be taking a fresh look at direct traffic in modern Google Analytics. As well as exploring the myriad ways in which referrer data can be lost, we’ll look at some tools and tactics you can start using immediately to reduce levels of direct traffic in your reports. Finally, we’ll discover how advanced analysis and segmentation can unlock the mysteries of direct traffic and shed light on what might actually be your most valuable users.
In short, Google Analytics will report a traffic source of "direct" when it has no data on how the session arrived at your website, or when the referring source has been configured to be ignored. You can think of direct as GA’s fall-back option for when its processing logic has failed to attribute a session to a particular source.
To properly understand the causes and fixes for direct traffic, it’s important to understand exactly how GA processes traffic sources. The following flow-chart illustrates how sessions are bucketed — note that direct sits right at the end as a final "catch-all" group.
Broadly speaking, and disregarding user-configured overrides, GA’s processing follows this sequence of checks:
AdWords parameters > Campaign overrides > UTM campaign parameters > Referred by a search engine > Referred by another website > Previous campaign within timeout period > Direct
Note the penultimate processing step (previous campaign within timeout), which has a significant impact on the direct channel. Consider a user who discovers your site via organic search, then returns via direct a week later. Both sessions would be attributed to organic search. In fact, campaign data persists for up to six months by default. The key point here is that Google Analytics is already trying to minimize the impact of direct traffic for you.
Contrary to popular belief, there are actually many reasons why a session might be missing campaign and traffic source data. Here we will run through some of the most common.
The classic direct-traffic scenario, this one is largely unavoidable. If a user types a URL into their browser’s address bar or clicks on a browser bookmark, that session will appear as direct traffic.
Simple as that.
When a user follows a link on a secure (HTTPS) page to a non-secure (HTTP) page, no referrer data is passed, meaning the session appears as direct traffic instead of as a referral. Note that this is intended behavior. It’s part of how the secure protocol was designed, and it does not affect other scenarios: HTTP to HTTP, HTTPS to HTTPS, and even HTTP to HTTPS all pass referrer data.
So, if your referral traffic has tanked but direct has spiked, it could be that one of your major referrers has migrated to HTTPS. The inverse is also true: If you’ve migrated to HTTPS and are linking to HTTP websites, the traffic you’re driving to them will appear in their Analytics as direct.
If your referrers have moved to HTTPS and you’re stuck on HTTP, you really ought to consider migrating to HTTPS. Doing so (and updating your backlinks to point to HTTPS URLs) will bring back any referrer data which is being stripped from cross-protocol traffic. SSL certificates can now be obtained for free thanks to automated authorities like LetsEncrypt, but that’s not to say you should neglect to explore the potentially-significant SEO implications of site migrations. Remember, HTTPS and HTTP/2 are the future of the web.
If, on the other hand, you’ve already migrated to HTTPS and are concerned about your users appearing to partner websites as direct traffic, you can implement the meta referrer tag. Cyrus Shepard has written about this on Moz before, so I won’t delve into it now. Suffice to say, it’s a way of telling browsers to pass some referrer data to non-secure sites, and can be implemented as a <meta> element or HTTP header.
Let’s say you’ve launched a new landing page template and forgotten to include the GA tracking code. Or, to use a scenario I’m encountering more and more frequently, imagine your GTM container is a horrible mess of poorly configured triggers, and your tracking code is simply failing to fire.
Users land on this page without tracking code. They click on a link to a deeper page which does have tracking code. From GA’s perspective, the first hit of the session is the second page visited, meaning that the referrer appears as your own website (i.e. a self-referral). If your domain is on the referral exclusion list (as per default configuration), the session is bucketed as direct. This will happen even if the first URL is tagged with UTM campaign parameters.
As a short-term fix, you can try to repair the damage by simply adding the missing tracking code. To prevent it happening again, carry out a thorough Analytics audit, move to a GTM-based tracking implementation, and promote a culture of data-driven marketing.
This is an easy one. Don’t use meta refreshes or JavaScript-based redirects — these can wipe or replace referrer data, leading to direct traffic in Analytics. You should also be meticulous with your server-side redirects, and — as is often recommended by SEOs — audit your redirect file frequently. Complex chains are more likely to result in a loss of referrer data, and you run the risk of UTM parameters getting stripped out.
Once again, control what you can: use carefully mapped (i.e. non-chained) code 301 server-side redirects to preserve referrer data wherever possible.
Links in Microsoft Word documents, slide decks, or PDFs do not pass referrer information. By default, users who click these links will appear in your reports as direct traffic. Clicks from native mobile apps (particularly those with embedded "in-app" browsers) are similarly prone to stripping out referrer data.
To a degree, this is unavoidable. Much like so-called “dark social” visits (discussed in detail below), non-web links will inevitably result in some quantity of direct traffic. However, you also have an opportunity here to control the controllables.
If you publish whitepapers or offer downloadable PDF guides, for example, you should be tagging the embedded hyperlinks with UTM campaign parameters. You’d never even contemplate launching an email marketing campaign without campaign tracking (I hope), so why would you distribute any other kind of freebie without similarly tracking its success? In some ways this is even more important, since these kinds of downloadables often have a longevity not seen in a single email campaign. Here’s an example of a properly tagged URL which we would embed as a link:
https://builtvisible.com/embedded-whitepaper-url/?…_medium=offline_document&utm_campaign=201711_utm_whitepaper
The same goes for URLs in your offline marketing materials. For major campaigns it’s common practice to select a short, memorable URL (e.g. moz.com/tv/) and design an entirely new landing page. It’s possible to bypass page creation altogether: simply redirect the vanity URL to an existing page URL which is properly tagged with UTM parameters.
So, whether you tag your URLs directly, use redirected vanity URLs, or — if you think UTM parameters are ugly — opt for some crazy-ass hash-fragment solution with GTM (read more here), the takeaway is the same: use campaign parameters wherever it’s appropriate to do so.
This is a big one, and probably the least well understood by marketers.
The term “dark social” was first coined back in 2012 by Alexis Madrigal in an article for The Atlantic. Essentially it refers to methods of social sharing which cannot easily be attributed to a particular source, like email, instant messaging, Skype, WhatsApp, and Facebook Messenger.
Recent studies have found that upwards of 80% of consumers’ outbound sharing from publishers’ and marketers’ websites now occurs via these private channels. In terms of numbers of active users, messaging apps are outpacing social networking apps. All the activity driven by these thriving platforms is typically bucketed as direct traffic by web analytics software.
People who use the ambiguous phrase “social media marketing” are typically referring to advertising: you broadcast your message and hope people will listen. Even if you overcome consumer indifference with a well-targeted campaign, any subsequent interactions are affected by their very public nature. The privacy of dark social, by contrast, represents a potential goldmine of intimate, targeted, and relevant interactions with high conversion potential. Nebulous and difficult-to-track though it may be, dark social has the potential to let marketers tap into elusive power of word of mouth.
So, how can we minimize the amount of dark social traffic which is bucketed under direct? The unfortunate truth is that there is no magic bullet: proper attribution of dark social requires rigorous campaign tracking. The optimal approach will vary greatly based on your industry, audience, proposition, and so on. For many websites, however, a good first step is to provide convenient and properly configured sharing buttons for private platforms like email, WhatsApp, and Slack, thereby ensuring that users share URLs appended with UTM parameters (or vanity/shortened URLs which redirect to the same). This will go some way towards shining a light on part of your dark social traffic.
To summarize what we’ve already discussed, here are the steps you can take to minimize the level of unnecessary direct traffic in your reports:
Adhere to these principles, and it’s often possible to achieve a dramatic reduction in the level of direct traffic reported in Analytics. The following example involved an HTTPS migration, GTM migration (as part of an Analytics review), and an overhaul of internal campaign tracking processes over the course of about 6 months:
But the saga of direct traffic doesn’t end there! Once this channel is “clean” — that is, once you’ve minimized the number of avoidable pollutants — what remains might actually be one of your most valuable traffic segments.
For reasons we’ve already discussed, traffic from bookmarks and dark social is an enormously valuable segment to analyze. These are likely to be some of your most loyal and engaged users, and it’s not uncommon to see a notably higher conversion rate for a clean direct channel compared to the site average. You should make the effort to get to know them.
The number of potential avenues to explore is infinite, but here are some good starting points:
I hope this guide has been useful. With any luck, you arrived looking for ways to reduce the level of direct traffic in your reports, and left with some new ideas for how to better analyze this valuable segment of users.
Thanks for reading!
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!
Posted by tombennet
When it comes to direct traffic in Analytics, there are two deeply entrenched misconceptions.
The first is that it’s caused almost exclusively by users typing an address into their browser (or clicking on a bookmark). The second is that it’s a Bad Thing, not because it has any overt negative impact on your site’s performance, but rather because it’s somehow immune to further analysis. The prevailing attitude amongst digital marketers is that direct traffic is an unavoidable inconvenience; as a result, discussion of direct is typically limited to ways of attributing it to other channels, or side-stepping the issues associated with it.
In this article, we’ll be taking a fresh look at direct traffic in modern Google Analytics. As well as exploring the myriad ways in which referrer data can be lost, we’ll look at some tools and tactics you can start using immediately to reduce levels of direct traffic in your reports. Finally, we’ll discover how advanced analysis and segmentation can unlock the mysteries of direct traffic and shed light on what might actually be your most valuable users.
In short, Google Analytics will report a traffic source of "direct" when it has no data on how the session arrived at your website, or when the referring source has been configured to be ignored. You can think of direct as GA’s fall-back option for when its processing logic has failed to attribute a session to a particular source.
To properly understand the causes and fixes for direct traffic, it’s important to understand exactly how GA processes traffic sources. The following flow-chart illustrates how sessions are bucketed — note that direct sits right at the end as a final "catch-all" group.
Broadly speaking, and disregarding user-configured overrides, GA’s processing follows this sequence of checks:
AdWords parameters > Campaign overrides > UTM campaign parameters > Referred by a search engine > Referred by another website > Previous campaign within timeout period > Direct
Note the penultimate processing step (previous campaign within timeout), which has a significant impact on the direct channel. Consider a user who discovers your site via organic search, then returns via direct a week later. Both sessions would be attributed to organic search. In fact, campaign data persists for up to six months by default. The key point here is that Google Analytics is already trying to minimize the impact of direct traffic for you.
Contrary to popular belief, there are actually many reasons why a session might be missing campaign and traffic source data. Here we will run through some of the most common.
The classic direct-traffic scenario, this one is largely unavoidable. If a user types a URL into their browser’s address bar or clicks on a browser bookmark, that session will appear as direct traffic.
Simple as that.
When a user follows a link on a secure (HTTPS) page to a non-secure (HTTP) page, no referrer data is passed, meaning the session appears as direct traffic instead of as a referral. Note that this is intended behavior. It’s part of how the secure protocol was designed, and it does not affect other scenarios: HTTP to HTTP, HTTPS to HTTPS, and even HTTP to HTTPS all pass referrer data.
So, if your referral traffic has tanked but direct has spiked, it could be that one of your major referrers has migrated to HTTPS. The inverse is also true: If you’ve migrated to HTTPS and are linking to HTTP websites, the traffic you’re driving to them will appear in their Analytics as direct.
If your referrers have moved to HTTPS and you’re stuck on HTTP, you really ought to consider migrating to HTTPS. Doing so (and updating your backlinks to point to HTTPS URLs) will bring back any referrer data which is being stripped from cross-protocol traffic. SSL certificates can now be obtained for free thanks to automated authorities like LetsEncrypt, but that’s not to say you should neglect to explore the potentially-significant SEO implications of site migrations. Remember, HTTPS and HTTP/2 are the future of the web.
If, on the other hand, you’ve already migrated to HTTPS and are concerned about your users appearing to partner websites as direct traffic, you can implement the meta referrer tag. Cyrus Shepard has written about this on Moz before, so I won’t delve into it now. Suffice to say, it’s a way of telling browsers to pass some referrer data to non-secure sites, and can be implemented as a <meta> element or HTTP header.
Let’s say you’ve launched a new landing page template and forgotten to include the GA tracking code. Or, to use a scenario I’m encountering more and more frequently, imagine your GTM container is a horrible mess of poorly configured triggers, and your tracking code is simply failing to fire.
Users land on this page without tracking code. They click on a link to a deeper page which does have tracking code. From GA’s perspective, the first hit of the session is the second page visited, meaning that the referrer appears as your own website (i.e. a self-referral). If your domain is on the referral exclusion list (as per default configuration), the session is bucketed as direct. This will happen even if the first URL is tagged with UTM campaign parameters.
As a short-term fix, you can try to repair the damage by simply adding the missing tracking code. To prevent it happening again, carry out a thorough Analytics audit, move to a GTM-based tracking implementation, and promote a culture of data-driven marketing.
This is an easy one. Don’t use meta refreshes or JavaScript-based redirects — these can wipe or replace referrer data, leading to direct traffic in Analytics. You should also be meticulous with your server-side redirects, and — as is often recommended by SEOs — audit your redirect file frequently. Complex chains are more likely to result in a loss of referrer data, and you run the risk of UTM parameters getting stripped out.
Once again, control what you can: use carefully mapped (i.e. non-chained) code 301 server-side redirects to preserve referrer data wherever possible.
Links in Microsoft Word documents, slide decks, or PDFs do not pass referrer information. By default, users who click these links will appear in your reports as direct traffic. Clicks from native mobile apps (particularly those with embedded "in-app" browsers) are similarly prone to stripping out referrer data.
To a degree, this is unavoidable. Much like so-called “dark social” visits (discussed in detail below), non-web links will inevitably result in some quantity of direct traffic. However, you also have an opportunity here to control the controllables.
If you publish whitepapers or offer downloadable PDF guides, for example, you should be tagging the embedded hyperlinks with UTM campaign parameters. You’d never even contemplate launching an email marketing campaign without campaign tracking (I hope), so why would you distribute any other kind of freebie without similarly tracking its success? In some ways this is even more important, since these kinds of downloadables often have a longevity not seen in a single email campaign. Here’s an example of a properly tagged URL which we would embed as a link:
https://builtvisible.com/embedded-whitepaper-url/?…_medium=offline_document&utm_campaign=201711_utm_whitepaper
The same goes for URLs in your offline marketing materials. For major campaigns it’s common practice to select a short, memorable URL (e.g. moz.com/tv/) and design an entirely new landing page. It’s possible to bypass page creation altogether: simply redirect the vanity URL to an existing page URL which is properly tagged with UTM parameters.
So, whether you tag your URLs directly, use redirected vanity URLs, or — if you think UTM parameters are ugly — opt for some crazy-ass hash-fragment solution with GTM (read more here), the takeaway is the same: use campaign parameters wherever it’s appropriate to do so.
This is a big one, and probably the least well understood by marketers.
The term “dark social” was first coined back in 2012 by Alexis Madrigal in an article for The Atlantic. Essentially it refers to methods of social sharing which cannot easily be attributed to a particular source, like email, instant messaging, Skype, WhatsApp, and Facebook Messenger.
Recent studies have found that upwards of 80% of consumers’ outbound sharing from publishers’ and marketers’ websites now occurs via these private channels. In terms of numbers of active users, messaging apps are outpacing social networking apps. All the activity driven by these thriving platforms is typically bucketed as direct traffic by web analytics software.
People who use the ambiguous phrase “social media marketing” are typically referring to advertising: you broadcast your message and hope people will listen. Even if you overcome consumer indifference with a well-targeted campaign, any subsequent interactions are affected by their very public nature. The privacy of dark social, by contrast, represents a potential goldmine of intimate, targeted, and relevant interactions with high conversion potential. Nebulous and difficult-to-track though it may be, dark social has the potential to let marketers tap into elusive power of word of mouth.
So, how can we minimize the amount of dark social traffic which is bucketed under direct? The unfortunate truth is that there is no magic bullet: proper attribution of dark social requires rigorous campaign tracking. The optimal approach will vary greatly based on your industry, audience, proposition, and so on. For many websites, however, a good first step is to provide convenient and properly configured sharing buttons for private platforms like email, WhatsApp, and Slack, thereby ensuring that users share URLs appended with UTM parameters (or vanity/shortened URLs which redirect to the same). This will go some way towards shining a light on part of your dark social traffic.
To summarize what we’ve already discussed, here are the steps you can take to minimize the level of unnecessary direct traffic in your reports:
Adhere to these principles, and it’s often possible to achieve a dramatic reduction in the level of direct traffic reported in Analytics. The following example involved an HTTPS migration, GTM migration (as part of an Analytics review), and an overhaul of internal campaign tracking processes over the course of about 6 months:
But the saga of direct traffic doesn’t end there! Once this channel is “clean” — that is, once you’ve minimized the number of avoidable pollutants — what remains might actually be one of your most valuable traffic segments.
For reasons we’ve already discussed, traffic from bookmarks and dark social is an enormously valuable segment to analyze. These are likely to be some of your most loyal and engaged users, and it’s not uncommon to see a notably higher conversion rate for a clean direct channel compared to the site average. You should make the effort to get to know them.
The number of potential avenues to explore is infinite, but here are some good starting points:
I hope this guide has been useful. With any luck, you arrived looking for ways to reduce the level of direct traffic in your reports, and left with some new ideas for how to better analyze this valuable segment of users.
Thanks for reading!
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!
In April last year, Google launched their mobile-friendly update, which favoured mobile-friendly websites in search results delivered on mobile devices. Much further back, in 2010, Apple’s Steve Jobs claimed that the post-PC era had arrived. In accordance with such claims, desktop and laptop computer sales have steadily been dropping ever since as more and more consumers turn to the small screen to fulfil their everyday computing needs.
Today, it’s not uncommon for the smartphone to be the most powerful computer in a household, and there’s also been an unprecedented rise of the mobile-only user who exclusively uses a smartphone and/or tablet to access the Internet. Particularly among millennials, the small screen has proven very pervasive in everyday life. Perhaps, given the current trends in the market place, it’s no wonder that the mobile-first approach for digital marketing strategies has been so hyped up in recent years.
A mobile-first approach only considers users of small, touch-screen devices such as smartphones and tablets. Marketers who use this approach don’t give any thought to things like keyboards, mice and large displays, apparently thinking that they’ve gone the way of the dodo. In reality, however, it can be argued that the mobile-first approach is the wrong one. What matters are screens rather than devices. There isn’t ever going to be a mobile-only world, just a world with more options.
There are now more ways to connect to the Internet than ever before, but different devices are designed to do different things. Almost no one conducts intensive research online on the small screen, just as no student is going to type out an entire dissertation on one. On the other hand, people aren’t going to be using the large screen while they’re out and about looking for a place to eat or a particular shop in the high street. Mobile might be primary, but only for certain tasks.
When it comes to everyday consumer services, mobile usage is undoubtedly much higher. As such, the mobile-first approach can work, to a degree, in cases where the vast majority of a brand’s target audience predominantly uses the small screen. At the same time, you’ll likely still end up alienating a lot of potential customers if your website provides a sub-par experience on the larger screen. For example, even predominantly mobile users are more likely to use the large screen while at work.
These days, the average person spends more than two hours per day using their smartphones and a bit over an hour and a half in front of a desktop or laptop computer. Since desktop computers continue to dominate in the workplace, those with typical office jobs will likely spend much more time in front of the big screen than anything else. The TV also remains a major part of many people’s lives, and many consumers even use their TVs for browsing the Web.
Ultimately, the mobile-first approach is doomed to fail in all but a handful of niche industries with very specific target demographics. In other industries, the approach might enjoy some limited success for the time being, but again, this very much depends on your target demographic. Instead, your primary focus should be on developing scalable websites and apps that offer an optimal experience on all devices.
