Adobe Predicts Online Mobile Christmas Shopping Will Break New Records This Year

More than 50% of all web traffic will be from smartphones and tablets.

Adobe Analytics has released its online shopping predictions for the upcoming holiday season and have estimated that online sales will be some $107.4 billion in the United States, alone – an increase of almost 15% on 2016.

But the big revelation is that 54% of all web traffic to retailers’ websites will come from mobile devices such as smartphones and tablets, exceeding those from laptops and desktop computers.

Insight is from Adobe’s artificial intelligence and machine learning network – Adobe Sensei. (Not via Santa.)

Mobile sites and integration

However, when it comes to final purchases, customers will still be more likely to actually buy their online Christmas shopping using a desktop computer, and that websites with fully optimized mobile sites are far more likely to be the recipient consumer of dollars, as a result.

Adobe have stated that retailers with better mobile websites and easier mobile payment integration will benefit the most. The online trend may also have game-changing implications for mobile advertising, which is set to be allocated an increasing share of ad sales.

What else is Adobe saying?

Adobe also claim, according to their research, that this year’s Cyber Monday will become the single largest online shopping day in history, and is expected to generate over $6,000,000,000 in sales, an almost 20% jump compared to 2016 alone.

Do Adobe have a crystal ball?

Yes, Adobe does pretty much have the PDF market cornered. No they don’t have a crystal ball, though they may hand out some form of glassware products at retirement. Honestly, I have no idea.

What Adobe does have, however, is Adobe Sensei, it’s very own Artificial Intelligence and machine learning network.

Adobe have been using Sensei to identify retail insights from trillions of data points, and based their conclusions on the in-depth analysis of one trillion visits to over 4,500 retail sites and 55 million SKUs.

According to Adobe, about 4/5 of every $10 that consumers spend online in the US goes through something called the Adobe Experience Cloud. Consequently, it’s hard to argue with their findings. Unless it’s all a conspiracy. But it probably isn’t. I mean, if it was, how would we know.

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However, when it comes to final purchases, customers will still be more likely to actually buy their online Christmas shopping using a desktop computer, and that websites with fully optimized mobile sites are far more likely to be the recipient consumer dollars as a result.

Adobe have stated that retailers with better mobile websites and easier mobile payment integration will benefit the most. The online trend may also have game-changing implications for mobile advertising, which is set to be allocated an increasing share of ad sales.

What else are Adobe saying?

That’s a good question. Go you for being so incredibly you today.

Adobe also claim, according to their research, that this year’s Cyber Monday will become the single largest online shopping day in history, and is expected to generate over $6,000,000,000 in sales, an almost 20% jump compared to 2016 alone.

Do Adobe have a crystal Ball? I thought they just did PDFs.

Yes, Adobe does pretty much have the PDF market cornered. No they don’t have a crystal ball, though they may hand out some form of glassware products at retirement. Honestly, I have no idea.

What Adobe does have however is Adobe Sensei, Adobe’s very own Artificial Intelligence and machine learning network.

Adobe have been using Sensei to identify retail insights from trillions of data points, and based their conclusions on the in depth analysis of one trillion visits to over 4,500 retail sites and 55 million SKUs.

According to Adobe, about 4/5 of every $10 that consumers spend online in the US goes through something called the Adobe Experience Cloud. Consequently, it’s hard to argue with their findings. Unless it’s all a conspiracy. But it probably isn’t. I mean, if it was, how would we know.