“Automation and machine learning are a big emphasis on Google currently and our industry as a whole. The more we as practitioners can leverage these tools, the more time we can dedicate to higher-level strategy and other account growth opportunities”
– Josh Brisco, Sr. Manager, Retail Search Operations @CPC Strategy
Human beings are brilliant, undoubtedly. Our brains are equipped with the acute comprehension and analytical skills that grant us the ability to solve the most complex of problems. And for the few problems that were beyond our reach (or were too tedious to spark interest), we resorted to artificial intelligence and created machines. The irony, however, lies in the fact that machines turned out to be significantly more ‘intelligent’ and are now capable of accomplishing tasks that even human beings are unable to. Who’s brilliant now?
A War of Smarts!?
Before you gather all your insecurities and jump into an existential crisis, do ponder over the fact that machines are still a human creation, and therefore are still in our control. So we can assume that we are still superior. Phew.
However, there is no denying the unprecedented capabilities of artificial intelligence and machine learning. Our revered idol, Steve Jobs, regarded the machine as a “bicycle for the mind” which generally is understood to mean that just as a bike increases the efficiency of human-powered locomotion, machines increase human mental productivity and output.
The rapid advancement of artificial intelligence and machine learning has led us into a period of great change- a fourth industrial revolution, perhaps. Every industry is being impacted by these drastic changes as machines take up leading roles in processing the multitude of data surrounding every kind of interaction, including human interactions with technology.
A Union of Smarts
Setting aside your humanly need to feel superior, do accept that it would be deeply imperceptive to not credit machines for their distinguished dexterity at finding patterns in historical data and using them to predict the future.
Machine learning is infiltrating every industry but its benefits are significantly great for digital advertising. Due to its ability to collect data, analyze and learn from it, AI provides valuable customer insights to companies and is transforming the world of digital strategies. Search Engine Marketing (SEM) is one aspect of digital marketing that has benefited greatly from the intervention of artificial intelligence and machine learning. But in order to understand the importance of this intervention, it is imperative to understand the workings of SEM first. Bear with me, it will be worth it.
Essentially, SEM is the marketing tactic that advertises the product or service of a company through the use of paid ads that appear on search engine results pages (SERPs). Basically, the marketers bid on certain keywords that a consumer might enter while looking for specific products or services on search engines like Google. These keywords enable the marketers to display their ads alongside the results for those search queries; thus enhancing the probability of gaining a customer. Such ads are also known as pay-per-click ads (PPC) and they come in various formats, for example, they can be text based or image/video based. Their main purpose, however, is to enable the consumer to see important information about the product at a glance.
SEM is undoubtedly the most effective way to grow your business as it offers marketers the unparalleled opportunity to display their ads in front of the right consumer at precisely the right time– greatly increasing the probability of conversion.
However, optimizing SEM requires meticulous research and data handling. This is where artificial intelligence comes in with its infinite abilities. Machine learning algorithms take over the redundant fundamentals of bid and budget management by diving into mass data, analyzing it and generating effective strategies. There are ample ways AI intervenes in SEM to improve results from standardized tasks. Some of them are listed below:
1. Understanding and Targeting Audiences
A key aspect of marketing is the audience. Knowing the needs, preferences and thought patterns of the target audience gives the marketer a significant advantage. In the olden days, a marketer’s best bet was to place an advertisement at a billboard or some other place where it would be visible to the greatest number of people. This method was unoptimum because it failed to take into account numerous other variables and also resulted in resources wasted on a large audience that was never interested in the first place.
In this technological age, however, other significant developments have taken place that minimize the wastage of resources by narrowing down on the target audience and morphing the advertisements in a way that caters to the desires of that particular audience. This process, however, is extremely time consuming and strenuous, which is why marketers resort to AI algorithms for maximum efficiency. Machines have the ability to handle an exorbitant amount of consumer data in no time. They automate and optimize the process by analyzing the data and uncovering trends that suggest the preferences and purchase intent of the audience. For instance, location-based marketing is one such example where artificial intelligence is used to extricate the target audience based on their geographical location. Algorithms are then designed to analyze the preferences of that audience in accordance with their location and then advertise products that would cater to them. This explains how a consumer begins to receive advertisements for winter clothing as soon as the temperature drops in his/her geographical area. Machine learning also has the ability to identify new segments of the target audience by further analyzing the data patterns and uncovering new commonalities and relationships about the audience that regular data analysis is incapable of.
For example, Microsoft Graph employs AI algorithms across a multitude of anonymous data signals from search and web activity. Similarly, LinkedIn utilizes data from professional profiles and demographics to identify which audiences would be worth reaching out to. Companies can now have access to CRM data, create prospect audiences, identify qualified leads and monitor audience performance- all owed to AI technology.
2. Optimizing Marketing Content
The ability to understand the prospective audience opens new doors for marketing. It enables the marketers to curate advertising content that is relevant to the interests of that particular audience, and instead of relying on extraneous manual labour for this task, marketers resort to machines. AI is used to efficiently automate the testing of various types of content and determine which content resonates best with the target audience. By tracking consumer trends and producing actionable insights, these AI tools allow the marketer to spend time streamlining tasks to reach more leads with the content. These tools also have the ability to enhance the PPC campaigns by sifting through data to uncover information that reveals the metrics needed to drive your business forward. It also enables you to make strategic decisions based on KPIs and achieve the optimum PPC goals you designate for your business. For instance, Google Ads incorporates AI into their ad rotation settings. Setting the ad version to ‘optimize’ automatically optimizes the ads for individual auctions using signals like keyword, search term, device and location. Then as Google Ads collects more data about ad performance, machine learning algorithms determine statistically which ads are likely to perform better.
3. Predictive Lead Scoring
Lead scoring refers to the process of attributing a numerical score to a lead, based on a variety of behaviors and other factors. Basically, it is a method used to qualify leads and highlight priorities. However, accurately and consistently interpreting the data is an exacting and time consuming process for marketers. Along with that, there is also the probability that the marketing team’s own assumptions and biases might taint the process. Therefore, it is again to rely on the expertise of AI. Machine learning is leveraged to provide the marketers with extensive knowledge regarding the customers and also generate ways to target the most qualified leads which results in ample saved time and significantly higher revenue streams. By utilizing both historical data along with predictive intelligence, machine learning tools enable the marketers to create predictive models that determine future trends accurately. What happens is the machine algorithm runs through the customer database, identifies trends and patterns, and builds a prediction model from the given data. It even draws correlations between generic lead characteristics and identifies valuable prospects even before they express strong intent of purchase– thus enabling the marketing team to focus on those prospects.
4. Keyword Selection
A keyword, certainly, is a key component of Search Engine Marketing tactics. However, narrowing down the right keywords for your campaign is a difficult task as a consumer’s product range spans over a range of different items, and includes various ways that he or she searches for them. Machine learning automates the process of researching and selecting effective keywords, thus making the process significantly easier. It transforms this consumer data into relevant strategic insights by classifying millions of keywords into a complex product hierarchy. AI tools provide extensive information on keywords regarding their value for organic and paid research along with the CPC, volume, number of results, trend and ad copies for the queried term. and present the marketers with popular and effective keywords that would optimize your ads. Thus, with the help of AI, marketers are able to select the keywords that would prove most effective for your marketing strategy. It can therefore be stated that AI holds the key(word) to a successful campaign. No regrets here. Okay, maybe some regrets.
5. Leveraging Ad Spend
As the name suggests, ad spend refers to the amount of money that is spent advertising for a product or a service. A successful ad campaign entails lesser ad spend and a greater ROI, however, achieving this benchmark is not easy. Ads often gain a substantial amount of clicks, but fail to generate any sales or conversions. Such a campaign can prove to be disastrous for a company because all it leaves you with is a lack of money, a whole lot of sorrow and a gaping hole where your ROI could have been. Manually weeding out these ads would require the marketer to filter them out, analyze them and pause them; which is not only difficult to do if multiple accounts are being run simultaneously, but also deprives the marketer of the opportunity to spend time on creating an effective strategy. Again, AI intervenes to save the day (read: campaign). Efficient AI and machine algorithms can interpret previous performance factors and use statistical inference to estimate potential gains and losses, thus, have the ability to pause and abandon an ad before it even affects ROI. These tools can analyze at a molecular level as they have the ability to take into account various other individual segments such as mobile traffic, non-revenue producing browsers, ad variations and times/days that reveal negative performance. Non-performing factors are then fine-tuned or outright closed through this analysis, thus, saving the company from wasting an exorbitant amount of money.
There is no denying that AI has the unparalleled ability to manage SEM in ways that are unattainable without it, even for the most impeccable marketers. Machine algorithms have already turned into a mainstream feature used to carry out taxing tasks such as segmenting audiences and micromanaging keywords in SEM practices. Adopting AI technology into your marketing strategy is imperative in order to boost ROI and remain ahead in competition with the entire industry.
Do not lag behind!