10 Tech Trends for Marketing Teams to Watch

  • Digital marketing is core to many businesses’ strategies, and the technology that supports these efforts is continually evolving.
  • Some existing trends will continue, including the growing importance of long-form educational content, chatbots and live chat, and voice search.
  • New emerging trends include Google’s push for a cookieless future.
  • This article is for small business owners and digital marketers who want to know about major trends and what to focus on in their marketing efforts.

While many principles of marketing remain the same each year, the tools businesses use to achieve marketing success vary greatly over time. Newspaper advertising was once commonplace. Now, digital advertising and artificial intelligence play critical roles in the marketing tactics of businesses.

Every year, there are more technological trends for entrepreneurs to keep an eye on. Business owners who stay ahead of the curve might even find new heights of marketing success. Here are 10 trends we believe small businesses should take advantage of this year.

Let’s take a deeper dive into these trends and how they can benefit your business.

1. Authentic long-form content remains king.

In content marketing, the trend has been toward long-form, educational content that aims to help users rather than sell to them. That trend will only continue, with developments like Google’s Helpful Content Update, which rolled out late last year. The content that will perform the best is content that thoroughly answers the questions people have and guides them toward the right decision for their circumstances.

Sharing about topics that interest your customers is a great way to build brand awareness and customer loyalty. You can build trust by showing you care about more than just a sale. Whether your content takes the form of a social media post, a blog or an email blast, ensure a balance between highlighting your products and providing valuable, actionable advice.

Long-form authentic marketing is a great way to boost interest and engagement among your target audience.

2. Short-form video content is coming for the crown.

Although long-form educational content remains potent for blogging or podcasting, short-form video content is increasingly popular. Thanks to the rise of TikTok and Instagram Reels, users are increasingly attuned to short snippets of entertaining or informative video content. Brands can use this trend to speak to their audience quickly and effectively amid a sea of other video content.

As users’ attention is pulled in many directions at once and attention spans shorten, clever short-form video content can get a brand’s message across in a matter of seconds. To capture the widest swath of your audience, deploy long-form content for users who want to dive deep and educate themselves, but create short-form video content for users who are scrolling to kill time. 

3. Adoption of chatbots and conversational AI will increase.

Chatbots, as well as more sophisticated conversational AI, will continue to make their way into the market and become increasingly accessible for small businesses. These tools can answer customers’ basic questions at all hours

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online teams lift up women in tech

Tarika Barrett (centre) states that the technologies sector struggles to retain female employees.Credit: Girls Who Code

It is no secret that science, technology, engineering and arithmetic have a gender diversity dilemma. Little ones as young as six regard women as becoming fewer fascinated than boys in personal computer science and engineering (A. Grasp et al. Proc. Natl Acad. Sci. United states of america 118, e2100030118 2021), and ladies are a lot less possible than boys to take part in sophisticated maths and laptop or computer-science courses and programmes. In 2021, gals represented just 28% of the US computing workforce, according to data from the Countrywide Middle for Girls & Data Technological know-how in Boulder, Colorado, and they accounted for 26% of US doctoral degrees granted in maths and laptop science, in accordance to the National Science Foundation’s Survey of Earned Doctorates.

Exacerbating this disparity are place of work activities of sexism, racism and other varieties of harassment — not to mention the ‘motherhood penalty’. Moms in the place of work receive a lot less than fathers do, and staying a dad or mum decreases women’s possibilities of promotion as properly as their access to qualified development possibilities and occupation advancement.


Closing this gender gap will require more than just training and teaching. It will also involve mentorship and a experienced network. “You simply cannot be what you simply cannot see,” states Tarika Barrett, an education reformer in New York Metropolis and main govt of the non-profit organization Women Who Code. The team is just one of a number of that intention to assistance women from under-represented communities to faucet into the social capital necessary for office good results in personal computer science.

These groups enable learners to prepare for interviews, share work alternatives and study collaboratively on superior programs. Potentially most importantly, they deliver a space for ladies, trans guys and non-binary men and women, who knowledge the brunt of gender-based mostly discrimination, to vent and share their workplace struggles. Various of these communities have made sturdy online communities on collaboration platforms these types of as Slack, through which they intention to interact and help their associates. “I just cannot underscore how critical this neighborhood is for girls and non-binary people,” Barrett says. “When they are sensation as while they just cannot persist in the area, they have that local community to lean on, coupled with their computer-science experience.”

Mother nature spoke to the leaders of four these kinds of teams about the problems they facial area, allyship (see ‘About allyship’) and the require for systemic change.

TARIKA BARRETT: Take action to tackle the gender gap

Chief govt of Girls Who Code in New York City.

Section of what we do at Women Who Code is teach pc science. We also operate to dispel the notion that ladies and individuals from minority teams do not have a seat at the desk as technologists. It is about constantly interrogating stereotypes about who belongs in

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Report: Personal computer eyesight teams globally say tasks are delayed by insufficient facts

Listen to from CIOs, CTOs, and other C-stage and senior execs on details and AI approaches at the Long term of Function Summit this January 12, 2022. Understand a lot more


According to new investigate by Datagen, 99% of laptop eyesight (CV) teams have experienced a machine studying (ML) task canceled owing to insufficient teaching details. Delays, in the meantime, show up truly ubiquitous, with 100% of teams reporting going through major undertaking delays due to inadequate coaching facts. The analysis also suggests that these schooling facts troubles occur in a lot of varieties and have an affect on CV teams in in close proximity to-equivalent measure. The top troubles seasoned by CV groups contain weak annotation (48%), insufficient domain protection (47%), and straightforward scarcity (44%).

The shortage of sturdy, area-distinct education knowledge is only compounded by the point that the industry of computer vision is lacking lots of properly-described standards or greatest tactics. When asked how teaching info is typically gathered at their organizations, respondents exposed a patchwork of resources and methodologies are being utilized each throughout the industry and within just individual organizations. No matter if synthetic or true, collected in-dwelling or sourced from community datasets, organizations show up to be using any and all data they can in purchase to prepare their laptop or computer vision models.

Nonetheless, laptop or computer eyesight teams have previously determined and started to embrace synthetic data as a option. Ninety-6 % of CV groups noted possessing presently adopted the use of artificial knowledge to assist practice their AI/ML models. Yet, the high quality, source, and proportion of artificial details that’s applied continues to be highly variable across the area, and only 6% of groups presently use artificial facts completely.

This wave of artificial knowledge adoption is consistent with a selection of modern field studies predicting that 2022 will be a breakout yr for synthetic info. This developing consensus definitely bodes effectively for pc vision’s many, eagerly awaited programs. In point, it’s doable that these systems are a lot nearer to fruition than they may possibly appear to be. Who is aware of? Possibly we’re just a couple of fantastic datasets away from a driverless environment.

The report draws on the conclusions of an online survey of 300 computer eyesight gurus symbolizing 300 unique companies.

Go through the full report by Datagen.

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Two Chinese teams claim to have reached primacy with quantum computers

The Pan team’s optical quantum computer uses a 144-mode interferometer to solve a Gaussian boson sampling problem with a factor-of-1024 speedup in computational time relative to a classical computer. Credit: Chao-Yang Lu/University of Science and Technology of China, via Physics

Two teams in China are claiming that they have reached primacy with their individual quantum computers. Both have published the details of their work in the journal Physical Review Letters.

In the computer world, quantum primacy is the performance of calculations that are not feasible on conventional computers—others use the term “quantum advantage.”

Over the past several years, several working with quantum computers have claimed to have reached primacy, but thus far have been met with skepticism due to questions about whether the algorithm used was the best choice possible, including the one used by Google. In this new effort, both teams are claiming that their computers leave no room for doubt.

Both of the teams in these new efforts were working at the Hefei National Laboratory for Physical Sciences at the University of Science and Technology of China, and both were led by physicist Jian-Wei Pan, who has become well known for his work with quantum entanglement.

In both efforts, the goal was to build a quantum computer capable of calculating the output probabilities of quantum circuits—a task that is relatively simple for a conventional computer to perform when there are just a few inputs and outputs. It grows increasingly difficult as the numbers rise until it becomes unfeasible.

In the first effort, the researchers used a photonic approach in building their computer. To tackle the problem of estimating output probabilities, the team used Gaussian boson sampling as a way to analyze the output. In this case, output from a 144-mode interferometer. Under this scenario, there could be 1043 possible outcomes. The researchers claim their machine was capable of sampling the output 1023 times as fast as a supercomputer, which, they further claim, shows quantum primacy.

The second effort involved creating a superconductor-based that was capable of calculating using 66 qubits—only 56 of them were used, however. Still, the researchers found the machine capable of estimating sample calculations up to 1000 times as fast as the best supercomputers, which, they claim, shows that they achieved primacy.


Chinese photonic quantum computer demonstrates quantum supremacy


More information:
Han-Sen Zhong et al, Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light, Physical Review Letters (2021). DOI: 10.1103/PhysRevLett.127.180502

Yulin Wu et al, Strong Quantum Computational Advantage Using a Superconducting Quantum Processor, Physical Review Letters (2021). DOI: 10.1103/PhysRevLett.127.180501

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