Intrusive marketing is dying fast in this age, where consumer experience is the focus. It’s giving way to humanized marketing, powered by artificial intelligence.
Now, brands don’t have one-way monologues wit consumers; they have dialogues, where the consumers speak their mind. This is the era of conversations.
However, this change has not been an incremental one. It’s been a sudden behavioral shift which is drastically changing the way we do business and the way we live.
Interestingly, there is another shift that is taking place in the marketing space – the focus has moved from technology to design.
When this happens, when a vital new platform goes from being academically interesting to mainstream interesting is the time to leverage and build on it. And that’s what’s happening with AI right now.
“Ask and you shall receive” -The new mantra for improved customer experience
Marketers and agencies are meant to be storytellers and strategists. They need to look at strategy, to determine where best to place a product, identify the audience, decide the messaging that will resonate most with them and uncover the best methods to move them to act.
Instead, they end up spend a good deal of their time trying to make sense of all the information and deciding spends based on hypotheses and data from digital media.
As data becomes the foundation for marketing decisions, digital marketers are having to sift through unprecedented quantities of it.
On the other hand, the progressive integration of technology into the physical world has created new consumer interactions that are simpler and more instantaneous. The outcome of this?Already high consumer expectations will be higher than ever.
This will pose a challenge for brands; but it will also present a great opportunity.We’re getting closer to a point where campaigns and customer interactions can be made more relevant end-to-end— right from planning, creative messaging and media targeting,through to the retail experience.
We will be able to consider all relevant consumer insights, from their color and tone preferences, to their purchase history and purchase context. And all of this will be optimized, in real-time.
For marketers and salespeople, AI and ML present great opportunities to improve day-to-day functions, act in a more targeted fashion, become more efficient at their job, get creative, and allow their businesses to uncover customer trends that were impossible to extract in the past. The possibilities are truly endless.
MAKING SENSE OF SILOED DATA FROM MULTIPLE PLATFORMS
Consider this... A user has an issue with a recently purchased product she bought through an app after coming across paid ads on Instagram.
She reports the grievance on Twitter and other social channels. However, while dealing with customer care, she must recount her experience all over again.Meanwhile, she’s still seeing paid ads on social media because the brand’s social data is disconnected from their CRM data.
Such experiences irritate valued customers with irrelevant content, while wasting valuable ad spend on consumers who are either already converted or are guaranteed not to convert. And all this is because data stays siloed, and is not brought together comprehensively.
A campaign with good messaging first needs a targeted audience that is statistically more likely to convert. By applying ML across all channels, brands receive not only those segments that have bought sneakers in the past, but a break down of those segments into hundreds of micro-segments, each with a unique combination of demographics, interests, and observed behaviors.
Also Read: The ultimate guide to influencer marketing
This is the closest thing we have to a 1:1 type of interaction today. ML should not only identify potential customers, but should estimate the likelihood of them actually making a purchase, identifying the websites they’re more likely to visit and seeing your display ad on, and determining an appropriate bid.
SEARCH (WEB&VOICE) AND PROGRAMMATIC AD BUYING
This approach can be extended to search campaigns as well. ML technology should be able to research thousands of keywords, test them in small campaigns, and optimize their use according to the results - all while larger campaigns are being managed and optimized.
Also, keywords can be tested for effectiveness with not only users, but with search algorithms as well.A good autonomous algorithm will look for keyword combinations that earn the highest quality score from Google, for instance, and will therefore improve the success rate when bidding for search terms.
Also, today there is a change in search behavior – more people are using voice worldwide. This means, SEO professionals have to make sure that their business is at the top of search results.
As more people bypass the search screen using voice search, the mechanics of search are transforming. Voice search enables businesses to be more discoverable in local searches, so marketers need to set up their website and content to appear when someone seeks a local business.
Google Ad Words is already using AI, in the form of its automated bidding system. Advertisers can automatically bid for the lowest possible cost per click (CPC) to efficiently capture traffic from Google results.
Going forward, programming advertising will make up the majority of ad buying.But, ML should be able to handle the bidding, integration, management, and execution of ad campaigns across platforms - from email, to search engines and social media.
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such as Machine Learning and Deep Learning by building affordable, people focused, design-first AI
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