Although conversion rate optimization (CRO) is nothing new, adopting new technologies to better enhance your CRO practices can seem a little unfamiliar and challenging for marketers. However, when it comes to utilizing predictive analytics and machine learning, the benefits to your conversion rates can be significant.
Through analyzing user behaviour and entrusting technology to make educated decisions about your website’s and funnel’s performance, it’s possible to provide a massive boost to your funnel. This can be particularly important for businesses as we begin to transition towards the era of the ‘new normal,’ away from the COVID-19 pandemic and the long periods of social isolation that affected business models worldwide.
Data illustrates just how challenging CRO processes can be, with almost a quarter of businesses expressing the belief that it’s the biggest obstacle they face in creating a coherent conversion rate optimization model.
Emerging technologies like predictive analytics and machine learning are evolving in a way that has the potential to redefine CRO as we know it. How can this advanced tech change how we win conversions? Let’s take a look at some key methodologies and use cases:
Appealing to The Right Customers With Predictive Lead Scoring
Traditionally, sales teams will manually assign a score to their leads based on how likely each individual is to convert. While these scores can be based on many metrics like age, gender, occupation and other behavioural traits like online interactions, click-throughs and email open rates, the approach can be far too generalized.
Rather than showing businesses the best leads available to them, traditional lead scoring is typically better at dismissing bad leads than spotting high potential ones. The scoring system is also fairly arbitrary and based more on individual intuition than any actionable data or analytics.
Predictive lead scoring, however, relies on analytics to cherry pick data from multiple sources like CRM systems, marketing automation platforms and social media, and then assigns a standardized score based on algorithmically generated predictions based on buying behaviour.
As the algorithm is continually working with new data, it also learns and adapts as it goes based on the real-time data around it. This means that the technology will become more accurate over time as it processes more data and leads.
The Who? What? Where? When? Why? of Conversions
Browser reports and device reports are excellent ways of getting the who, what, where, when and why of your online traffic.
Thanks to analytics platforms, it’s easy to work out which browser isn’t driving substantial conversions and why your conversion rates may be uneven based on where your traffic is accessing your site from. This data can be used to better anticipate how your website will be accessed and engaged with in the future and to make preemptive decisions about how to accommodate your visitors.
These offer comprehensive levels of data based on user sessions, their respective bounce rates, and the conversions they make. Information about each visitor’s operating system and browser are easily accessible so you can work on preemptively optimizing your site based on how your traffic interacts with it.
Chatbots Encapsulate The Power of Machine Learning in Action
We’re already seeing deep learning methods working their way into the world of conversion rate optimization, particularly in the form of AI chatbots which are increasingly winning popularity among businesses around the world.
Intelligent chatbots tap into their artificial intelligence backdrops to help users in a fast and efficient manner to generate better levels of customer support, making the conversion process shorter.
Although chatbots have been around for some time now, the quality of their performance in the early days was much more primitive than today. Deep learning has helped to revolutionize the quality of job that chatbots can do in learning from past interactions and altering its behaviour based on the type of questions that’s asked of it.
When a user consults a chatbot via a messaging platform, the bot can utilise natural language processing and machine learning to logically formulate how to escalate a query – whether it’s by delving into pre-programmed data, API from partners, or delegating the query to human respondents.
Today, the intelligence of chatbots has grown to the point that they’ve not only become focal points in supporting the customer journey, but they can also make for pretty effective legal consultants and educators, too.
It’s possible for businesses to set up chatbots that can adapt to customer behaviour of their own accord, and they only require some simple information to get going. If your business is looking to embrace digital transformation, there are plenty of excellent chatbot apps to get to grips with, and it’s worth exploring how well each will suit your CRO needs.
Dynamic Pricing For Businesses
Another way in which machine learning is redefining CRO is in how the technology has the ability to adjust prices in real time to tailor suit the customer that they are being displayed to. To do this, an algorithm taps into machine learning to calculate the ideal price point to generate the greatest level of profit while maximizing the chance of a conversion occurring.
Again, this is already coming into play in the world of eCommerce, and it may be possible for two users to check on the same product on their browsers in the same location to see different prices.
Multiple users could be browsing in the same geographical area, or even using the same WiFi network, but the dynamic pricing will be displayed differently to them due to their past behaviour and interactions.
If, for instance, the algorithm decides that there’s zero chance that you’ll make a purchase, you’ll see the full price. You’re also more likely to see the full price displayed if you are determined by the algorithm to be highly likely to make a purchase. However, if the same machine learning technology determines that you have some doubt regarding the product or its pricing based on your browsing history, it may automatically generate a discount upon your next visit.
As we begin to emerge from the pandemic, businesses that may have been affected by COVID-19 can begin to think about how they can adapt to the era of the ‘new normal.’ For some, profits may have taken a hit, while others fared relatively well during periods of lockdown. However, as more businesses look to digital transformation in order to win favour among the burgeoning online markets, we’re likely to see predictive analytics and machine learning take center stage.
When a dynamic price can make all the difference in expanding profit margins, and understanding the likeliness of a lead converting, it’s possible to save a small fortune in time and money with a fine-tuned CRO operation.