Will these 3 AI trends change CRO forever?
In the current digital recruitment climate, it’s harder to find someone who doesn’t need a great data scientist than someone who does. Marketing teams and agencies worldwide are frantically assembling the strongest teams they can build to meet the Big Data revolution head on, and devise strategies to harness maximum benefit for their brands and clients.
Fueled by an abundance of data and advances in Artificial Intelligence, the Conversion Rate Optimization space is in a state of near-perpetual disruption as Machine Learning creates endless possibilities to improve the online customer experience.
From the wealth of topics, here are 3 trends leading the changing demands in CRO.
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Chatbots
Let’s jump in straight with an example – Drift. Drift offers marketers AI-powered intelligent chatbots, which can not only provide answers to website visitors but also take an active role in the sales process by asking questions too. Drift bots can even book meetings on behalf of sales teams having answer customer enquiries, massively decreasing the sales cycle and also opening up 24/7 functionality.
IBM Watson also provides the engine for companies to build custom AI tools, and the field of automated conversational marketing tools continues to grow.
Whilst some CRO teams are up to their eyes in bewildering data, some have chosen to let the bots take over and guide customers to purchase in a fraction of the time any amount of UI site tinkering could achieve.
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Intelligent Traffic Optimization
Back in October 2017, Optimizely announced Stats Accelerator which claimed to allow companies to accelerate experimentation by up to 300%, and significantly reduce the workload involved in manually adjusting traffic to top-performing site or e-store variations. The magic happens via an algorithm which allows marketers to confidently make traffic switches with less data than previously required, offering huge potential for time-sensitive scenarios like flash or seasonal sales where manual data collection won’t cut it.
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Contextually-relevant Personalization
AI-driven advances in areas such as recommendation engines and other predictive algorithms have finally helped marketers break a long-standing deadlock, and we’re thankfully no longer offered variations of the exact item moments after checkout in online stores… at least, not as much as before. At last, algorithm-powered recommendations can leverage Machine Learning to add contextual relevance, ensuring no more AI gaffes.
Along with a detailed study of the methods used by e-commerce personalization giants such as Amazon to gain insight into industry best practices, CRO professionals can also keep pace with the market by researching purpose-built tools such as Nudgr and Sentient Ascend.