IBM predicts that 2019 will be the year of ‘martecheter’ – a digital-native, technically savvy professional, no longer calling a developer to implement some cutting-edge marketing tech stack.
Indeed, AI and machine learning are becoming a commodity technology. Plug and play solutions are plentiful on the market. Even SMEs can muster a budget to adopt those. For marketers, this increased accessibility stands for a long-awaited good-bye to the mundane and repetitive work. The new tools can make you more effective, creative and more focused on strategy and impact, rather than technical execution and analytics. SEO, in particular, is a ripe field for applying automation as the following three examples demonstrate.
Data analytics
The most successful marketers are already looking beyond data provided by Google Analytics alone. They also add CRM, conversion and content marketing data to their mix to pinpoint those profitable opportunities worth pursuing. Between 2017 and 2019, the median number of data sources used by marketers increased by 50%.
But the common fallacy that more data equals better decision-making still prevails. Despite plugging in more data sources, only 47% of marketers say that they managed to secure a unified view of customer data.
At this point, we clearly need to invest more in analysis, not analytics alone. Automation can help us turn the existing chaotic analytics processes into one integrated stream of readily applicable knowledge. That’s what predictive and prescriptive analytics is all about.
At present state, you can already automate the following SEP data analytics processes (based on example of what we achieve with Apollo Insights – our proprietary tool):
- Technical SEO audits and analysis
- Competitor intelligence gathering
- Keyword research and content gap analysis
- Conversions review and prioritised insights for optimisation
Content distribution
Organic reach keeps declining and new topics get saturated fast as more and more marketers join the content marketing bandwagon. Content fatigue is hardly a new term in the marketing industry, but it still hasn’t been properly addressed with a viable solution. As we’ve written before – consumers are receptive to well-executed content marketing, but they have a low tolerance for generic information delivered to them at the wrong time and in the wrong place.
Prospects now want to receive personalised advice, tailored specifically to where they are in their buying journey. Clearly, modelling such 1:1 conversations at scale without any automation is virtually impossible.
Beyond automating social media posts publishing at the optimal time, there are several other content marketing automations worth trying to expand your reach:
Content AI by Marketo relies on predictive analytics and machine learning to suggest “recommended content” for prospects browsing your blog.
Zemanta is a programmatic native advertising platform, suggesting relevant placements with top publishers.
Xink allows you to automatically manage and add new relevant content to email signatures of all your team members.
Influencer marketing and outreach
The estimated average ROI of influencer marketing in 2018 rounded up to $5,20 (£3.96) for every dollar spent. That’s significant if you benchmark it against the ROI of PPC ads ($2 for every $1 spent).
Beyond receiving the initial hype and sales from promotions on social media, blogger partnerships can also deliver a great kick in search rankings – especially if you choose to enlist a long-term brand ambassador to create and publish content for your brand over time.
The problem, however, is that scaling influencer marketing and digital outreach has always proven to be problematic. Lately, increasingly so as the influencer space is getting saturated by brands who end up rubbing elbows with the competition, promoted by the same influencer just a few posts earlier. Consumers are noticing that competition too. In fact, 52% of avid social media users state that they are tired of repetitive ads being pitched to them by influencers over and over again.
Automation, and more precisely machine learning, can help brands make better advertising matches and reduce the time spent on outreach. There’s no need to manually deal with sourcing, vetting and negotiating with online influencers when AI-powered tools can handle that chore for you.
Traackr allows you to assemble a dynamic database of global influencers based on brand impact and audience insights and automatically manage your campaigns.
Pitchbox allows you to run advanced influencer searches and receive a curated list of top publishers, complemented with SEO data from Ahrefs, SEMRush and other SEO tools.
Beyond that, AI is gradually becoming better versed in content creation, meaning that new tools will emerge to assist you with product listing creations, meta tags optimisation and other on-page SEO tasks.
Finally, Google and other search engines constantly evolve and change the rules of the game. Without relying on some degree of automation it would be tough to remain ahead of the competition. As we know well enough, those who are early to embrace the new features in the SERPs end up among the winners.
Michelle Hill is the marketing manager at Vertical Leap
// Featured in this article
Vertical Leap
Vertical Leap is the most effective search agency in the UK. We use data science and machine learning combined with experience and expertise to dig deeper, achieve more and operate at a scale that is …