SEO
Top 5 Marketing Strategies for International Companies 2024
Jari Vasko••19 min read
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As small and medium-sized businesses (SMBs) navigate the ever-changing digital landscape, it's crucial to stay ahead of the curve and adapt to the latest marketing trends. With the rise of AI-driven content creation, native advertising, and influencer marketing, the marketing landscape has become increasingly complex.
In this blog, we are exploring a few of the marketing trends of 2024, especially how smaller or medium-sized businesses could leverage and get ahead of the game.
In this blog, we'll delve into the top five marketing strategies and trends that SMBs can leverage to drive growth, increase conversions, and build brand awareness. From content marketing to search engine marketing, we'll explore the most effective ways to reach and engage with your target audience. Whether you're looking to boost your online presence, improve your website's conversion rates, or optimise your social media campaigns, this blog will provide you with insights and strategies.
Native advertising and sponsored content stand out as crucial strategies for businesses aiming to enhance their marketing efforts seamlessly. More than a third (36%) of marketers plan to increase their investment in native advertising in 2024, and 56% plan to continue investing the same amount. Only 9% say they'll decrease their investment. (HubSpot, 2024).
According to the Digital 2024 Global Overview Report, consumers increasingly favour organic content that is relevant to their interests. This trend underscores the importance of creating high-quality, engaging sponsored content that provides value to the audience while subtly promoting a brand's message.
Unlike traditional advertising, which is designed to interrupt and stand out, native advertising is designed to blend in and promote your brand to a new audience who might otherwise never learn about you. Partnering with platforms that have a strong native advertising framework can significantly enhance brand visibility and credibility.
Influencer marketing continues to be relevant. According to a survey conducted by HubSpot, 84% of marketers in their survey say that they will increase their investment in influencer marketing in 2024. The interesting take on influencer marketing from the point of an SMB is that instead of blowing up your advertising budget on influencers with millions of followers, you can invest in so-called micro-influencers with 10,000 to 100,000 followers.
Still relying on the research of HubSpot, marketers also saw the most success with micro-influencers mentioned above; 47% of influencer marketers reported so. Also showcasing the power of influencer marketing, 1 in 4 social media users bought a product based on an influencer’s recommendation in the past three months.
According to Datareportal, LinkedIn members have crossed 1 billion, making it still a very relevant advertising platform in 2024. Advertising resources show that the year-on-year increase is almost 14%. The demographic data indicates that users aged between 18 and 24 outnumber those above age 35, while companies’ advertising audience is between 25 and 34.
LinkedIn is especially effective in business-to-business (B2B) marketing, since 93% of B2B content marketers use LinkedIn for organic social marketing.
Even as a smaller business, you can network and build relationships, promote your content (blog posts, videos, images, etc…), use targeted advertising, and track your marketing efforts using LinkedIn’s analytic tools.
The rise of AI offers numerous opportunities in content marketing. It can increase the volume at which content is being produced. However, AI can also harm a brand’s reputation due to bias, plagiarism, or misalignment with brand values, as 60% of marketers share this concern.
Luckily, if AI is used just as an assistant with human eyes keenly observing the end result, these downfalls can be avoided.
When it comes to creating the content itself, short-form content seems to be here to stay and grow in relevance. Short-form content offers the highest ROI(Return of Investment) with 31%, so it doesn’t come as a surprise that marketers plan to invest more in it in 2024 (26%).
About 15-20% of global internet users report purchasing a product after seeing it advertised on social media, with a significant portion of this influence attributable to TikTok. The same scope can also be seen by looking at the statistics in the USA; 71.2% of users bought items they came across in their feeds ( Fit Small Business, 2024).
AI can be used in streamlining the creation of short-form content. For example, AI can create engaging snippets for social media, increasing the likelihood of shares and interactions.
Case studies provide detailed, real-world examples of how a product or service solves problems, making them highly effective for lead nurturing.
Case studies and blog posts are also high regarding the ROI; 15% (HubSpot, 2024). Short-form content is more on the side of B2C (Business to Consumer). By the listings of interodigital, on B2B (Business to Business), the most popular content types are short articles (94%), videos (84%) and lastly, case studies (78%).
AI can help create and distribute case studies to the right audience. AI can analyse which case studies generate the most engagement and suggest improvements or new topics based on audience interest.
Incorporating visuals and videos into blog posts can further enhance their appeal and effectiveness. Case studies are among the top ten types of content that generate the most backlinks, which are an important factor in improving a website's search engine rankings. Additionally, including case studies in email campaigns can result in a 19.3% increase in average open rates ( kraftshala, 2024).
Case studies are a versatile asset that can be strategically placed throughout the marketing and sales funnel. They tend to be most effective in the middle and bottom stages, where leads have identified problems and actively seek solutions. By providing detailed, real-world examples of how a product or service has addressed specific challenges, case studies can help potential clients understand the value and ROI of the offering. Incorporating client testimonials and data can further bolster the case study's impact.
In 2024, social media marketing trends are set to be driven by several key developments. Although short-form content’s popularity is peaking, one shift going forward this year is the resurgence of text-only posts, particularly on platforms like X(former Twitter) which highlights a transition from purely visual content back to traditional, text-based engagement.
This change suggests that audiences are seeking more substantive and direct forms of communication. Furthermore, AI-generated content is becoming increasingly prominent, with advanced tools creating more personalized and authentic interactions. These AI capabilities challenge traditional notions of authenticity by generating content that resonates deeply with users' preferences and behaviours.
Influencer marketing continues to evolve, with a significant move towards "communal success," where influencers foster genuine connections and produce highly relevant content for their audiences.
This approach emphasises building trust and community over mere promotional activities. Virtual influencers are also expected to become mainstream, offering brands new avenues for engagement and promotion within the expanding metaverse.
Another notable trend is the increasing use of social media platforms as search engines, providing personalised and contextualised user experiences. This shift is crucial for brands to optimise their content for discoverability on these platforms.
For small and medium-sized businesses (SMBs), these trends present unique opportunities. By engaging with niche influencers, SMBs can tap into highly targeted audiences, fostering deeper engagement and authenticity. Additionally, leveraging AI tools for content creation and customer interaction can streamline operations and enhance the personalisation of marketing efforts.
Moreover, the integration of AI in user-generated content (UGC) allows fans to remix and reinterpret brand materials creatively, pushing brands to adopt more flexible and imaginative content strategies.
AI-driven content creation helps SMBs expand their reach through community marketing. In 2024, AI, authentic influencers, and new platform features will shape social media marketing, giving businesses fresh ways to engage with audiences.
Search engine marketing (SEM) is a crucial aspect of digital marketing, and 2024 is expected to see significant changes in the way businesses approach SEM. One of the key trends is the rise of voice search optimisation. This shift towards voice search requires businesses to optimise their content for natural language queries, using long-tail keywords and natural language phrases to improve visibility.
Natural Language Processing (NLP) plays a crucial role in deciphering human language, enabling businesses to sift through extensive text data sourced from social media. By employing NLP algorithms, businesses can extract meaningful insights from social media posts, comments, and messages, revealing valuable information about user preferences, emotions, and areas of interest. (storylab.ai, 2024).
Additionally, the increasing use of artificial intelligence (AI) in SEM is expected to continue, with AI-powered tools being able to analyse vast amounts of data and provide insights into user behaviour and search patterns. This will enable businesses to create more targeted and personalized ad campaigns, increasing the likelihood of conversions.
Environmental impact is another important consideration for SEM strategy. Companies should ensure that their SEM activities do not harm the environment by reducing their carbon footprint, minimising waste, and using sustainable materials and practices. It's also crucial to avoid greenwashing, which involves making false claims about environmental sustainability. (2stallions, 2024).
Resilience is key for SEM strategy in 2024. Companies must be ready for unexpected events like natural disasters or cyber attacks and ensure their SEM activities can withstand such challenges. This includes having backup plans and redundancies in place to keep SEM activities running smoothly even during disruptions. (2stallions, 2024).
As a final remark, Google announced its new Search Generative Experience (SGE) at Google I/O in May 2023. This new AI-generated search development is an experimental approach to search that uses generative AI to aggregate information from the SERPs into a single answer.
This removes the need to click through individual web pages for answers, although the snapshot does credit top-page sources. It can also answer complex long-tail questions, so users don't need to make multiple searches.
Despite the changes and uncertainty that Google's SGE brings, optimizing for ranking is still crucial as SGE answers are generated using sources from top pages on Google. ( letterdrop, 2024).
Conversion optimisation, CRO, is the process of improving your website or app to get more visitors to take a desired action. The success of conversion rate strategy is defined by the conversion rate. Usually, something between 2% and 5% is considered a good rate, meaning only 2000 to 5000 clicks on your site from 100 000 clicks caused the wanted action.
Conversion rate optimisation consists of different parts, which optimistically can be automatized up to 99%
In **analytics and data gathering,tools like Google Analytics are used as eyes and ears, revealing how visitors interact with your site. What they click, where they drop off, how long they stay. **
Heatmaps and scroll maps can be used as visualised showings of potential areas of interest and friction points. User session recordings and form analysis are also important. So how can AI be used in this?
AI-powered tools can be used to generate custom reports on key metrics, highlight trends, and even offer actionable insights automatically, saving you hours of manual analysis. AI algorithms can be utilised to analyse historical data to predict future user behaviour and identify potential conversion roadblocks before they impact your bottom line.
Segmentation of the client base is crucial, especially in B2B marketing. Account-based marketing(ABM) is widely adopted in the B2B realm to target individual customers or specific groups. The goal is to influence a company's most important customers and their purchasing organizations through a targeted and personalized approach.
ABM differs from traditional mass marketing, which aims to reach as many contacts as possible simultaneously from a single company. Instead, ABM focuses on tailoring marketing efforts to specific accounts or groups of accounts, delivering a more personalized and relevant experience. By leveraging machine learning, segmenting can be based cost-effectively on a wider range of factors, creating hyper-targeted groups.
After data gathering, it is vital to understand your audience. AI-powered chatbots can be used to collect valuable user feedback through interactions that can ask qualifying questions and categorize responses, providing insights into user needs and pain points.
AI can also analyse text from customer reviews, social media posts, and surveys to gauge overall sentiment and identify areas where your website or product might fall short.
A/B testing (AKA split testing) and experimentation help you notice how minor changes affect your site. From visual effects to overall user experience, the goal of A/B testing is to identify changes that can improve user engagement, conversion rates, or other desired outcomes.
AI can be used in automating A/B testing; Platforms like OptiMonk allow you to set up and run A/B tests automatically, handling traffic allocation, statistical significance calculations, and even declaring winners.
Some platforms implement machine learning to adjust website elements (headlines, images, CTAs) in real-time based on user behaviour, constantly optimizing for conversions. AI can help especially in the aspects of back-end factors like performance, essentially the site speed, with image optimisation; Automatically resizing, cropping, and compressing images for optimal website performance without sacrificing quality.
Two things to mention especially on the side of CRO are cross-device compatibility and mobile-first product page design. Compatibility refers to the page or pages working properly with different devices. For example, text is large enough to read and clickable elements have sufficient padding for easy tapping. Mobile-first refers to designing pages with mobile devices being the priority instead of simply rearranging the desktop design.
An important thing about optimisation is the content itself provided. AI can also be used in content optimisation.
AI-powered content recommendations can deliver content to users based on their browsing history and preferences, increasing engagement and conversions. Dynamic content optimisation personalises website content in real-time based on user demographics, location, device, and behaviour to deliver a more tailored experience.
Data is the fuel of all marketing algorithms. Without data, they do not operate efficiently. It is also important to make sure the data itself is high-quality and the amount gathered is sufficient. If the data used for customisation is incomplete, incorrect, or biased, it may harm the results. Ensuring data cleanliness and integrity is crucial to avoid biased or misleading personalisation. AI algorithms are trained on historical data, which could potentially lead to using data ridden with biases.
As in all marketing, customers appreciate deep personalisation; Up to 71% of consumers demand personalised interactions. AI enables the use of hyper-personalising marketing efforts to cater to individual preferences and behaviours.
This includes personalised product recommendations, customised email marketing campaigns, and tailored content that resonates with the target audience. Email marketing is still effective, and because of that, it is a very potential part of data-driven marketing strategies.
Email marketing remains a dominant force in the digital marketing landscape. According to recent data, 41% of marketers identify it as their most effective channel, with the market expected to reach $12 billion by the end of 2024 (Sender, 2024).
Data-driven strategies, particularly segmentation and personalisation, are driving this growth. Segmented email campaigns demonstrate significantly higher engagement rates, with 30% more opens and 50% more click-throughs compared to unsegmented campaigns. Notably, 78% of marketers consider subscriber segmentation their most effective email marketing strategy.
Personalisation further amplifies email marketing efficacy. Personalised emails generate transaction rates six times higher than their non-personalised counterparts. Recognising this potential, 55% of marketers are prioritising increased personalisation efforts in the coming year (Sender, 2024).
By leveraging customer data for segmentation and personalisation, businesses can significantly enhance their email marketing performance and drive better results.
For many years, marketers could rely on data append processes, which meant utilising third-party sources to update or add missing information to their consumer database. In 2015, a study conducted by Forbes found out that 88% of marketers used data obtained by third parties to enhance their understanding of each customer.
Many giant tech firms have been taking steps toward a cookieless future, highlighting the importance of first-party data for segmentation and personalisation. Google, for example, in January 2020 announced its plans to phase out third-party cookies in Chrome, following Apple's similar move with Safari's Intelligent Tracking Prevention (ITP).
Despite repeated delays in the phase-out of third-party cookies, with the latest extension to April 23, 2024, the trajectory remains clear. This transition is not a passing trend but a fundamental shift in digital marketing practices. It is imperative for marketers, developers, and advertising executives to proactively seek transparent and well-communicated alternatives for data collection and targeting.
The focus is shifting towards first-party and zero-party data strategies, which prioritise user consent and direct information sharing. This approach not only addresses privacy concerns but also presents opportunities for more authentic customer engagement. Companies that adapt swiftly to this new paradigm will be better positioned to maintain effective digital marketing strategies in a post-cookie landscape.
As mentioned before, more consent-orientated ways to obtain data arezero-party data and first-party data. Zero-party data is data that users are willingly giving away to the company they trust. Companies need to offer customers something of value in exchange for this information.
Examples of zero-party data are preference centres, gamifying marketing experience with polls, challenges, and quizzes, personalised recommendations and loyalty programs.
Preference centresare customisable interfaces within companies’ digital properties (like a website or an email) where customers can manage their communication preferences. This includes choosing the type and frequency of communications they receive, as well as the channels through which they receive them (e.g., email, SMS, push notifications).
Preference centres offer transparency and control of data to customers, personalised experiences and tailored communications to each customer and improved segmentation.
Additionally, preference centres ensure compliance with data privacy regulations like GDPR( General Data Protection Regulation, European Union) and CCPA(California Consumer Privacy Act, California, USA) by providing clear and easy options for customers to manage their data and communication preferences.
Lastly, gathered details help improve marketing segments, making them more accurate.
Interactive content or gamified experience is a powerful tool to engage audiences and gather valuable data. There are many benefits to using interactive content.
A few to mention:
Interactive content generates twice as much conversion as passive content (Gitnux, 2024).
Interactive content improves learning and retention by promoting active learning. This directs users to think and make decisions.
Interactive content provides valuable data about user preferences, behaviours, and interests.
Interactive content is more shareable on social media platforms than static content, enhancing social sharing.
Lastly, interactive content can help a company stand out from the competition and create a positive brand image
Key in keepingpersonalised recommendations relevant is to make it as easy as possible for customers to update their willingly given zero-party data over time.
This can be achieved for example by periodic preference update emails or in-app prompts, allowing customers to manage their profiles and preferences in a central hub and incorporating zero-party data collection into key touchpoints like onboarding or post-purchase flows.
It is important to remember the value exchange and convey it to the customer; The more you get the customer to share their preferences, the more personalised and valuable the recommendations they receive in return. This fosters trust, engagement, and long-term loyalty.
Loyalty programsare one of the most effective ways for businesses to collect zero-party data. By offering rewards, discounts, or exclusive access in exchange for customer information, these programs create a transparent value exchange that encourages participation.
The more value a customer receives from the loyalty program, the more likely they are to provide detailed zero-party data. This data can then be used to deliver highly personalised product recommendations, content, and offers - further enhancing the customer experience and driving loyalty.
While zero-party data relies on information directly and voluntarily provided by customers, first-party data is collected through various direct interactions with your brand. Both types of data are crucial for creating personalised and effective marketing strategies in a cookieless world.
When it comes to first-party data, there are a few essential types that can be gathered; transactional, behavioural, demographic and social media interactions (inblog, 2023).
Transactional datais about purchase histories, average transaction values, and SKU ( Stock Keeping Unit) ranges. This data is key when a business wants to make relevant product recommendations to a customer or offer deals and promotions on optional timing.
Behavioural data has information on the actions of a user on a website, including pages visited, time spent on each page, clicked links and products added to the cart.
Demographic dataconsists of what you would expect; age, gender, location, occupation etc.
Feedback and surveys are direct feedback from consumers. Qualitative in nature, these can give insights that numeric data may miss.
Social media interactions are things such as likes, shares, comments and other engagements on social media platforms. These can give insights into a user's preferences, influencers they follow, and topics they're interested in.
What are the different technologies and tools that businesses can use in their journey towards data-driven marketing? One such tool is many of the customer data platforms (CDPs), which unify customer data from multiple sources into a single, comprehensive view. CDPs like Segment, Tealium, and Treasure Data allow businesses to collect, organise, and activate customer data to power personalised marketing campaigns.
Another essential tool is marketing automation platforms, such as HubSpot, Marketo, and Pardot. These platforms enable businesses to automate repetitive marketing tasks, such as email campaigns, lead nurturing, and social media posting, while also providing advanced analytics and reporting capabilities.
For more granular data analysis and optimisation, businesses can turn to tools like Google Analytics, Adobe Analytics, and Mixpanel. These platforms offer in-depth insights into customer behaviour, website performance, and marketing campaign effectiveness, allowing businesses to make data-driven decisions and continuously improve their strategies.
Finally, businesses should consider investing in AI-powered personalisation engines, like those offered by Monetate, Optimizely, and Dynamic Yield. These tools leverage machine learning to analyse customer data and deliver highly personalised product recommendations, content and offers in real-time.
By leveraging a comprehensive suite of data-driven marketing tools and technologies, businesses can ensure that their marketing algorithms are fueled by high-quality, accurate data, enabling them to create personalised, engaging experiences that drive customer loyalty and business growth.