What if you could use the data you already possess to better understand how to acquire new customers, retain current ones, and even get ex-customers to return? With Omniconvert, you can create a unique, personalized journey for each customer, beginning with your digital advertising through to their web site visit and purchases. Valentin Radu, Founder, and CEO explains how their platform drives those journeys and why the future belongs to the customer-centric businesses that take the time to understand and nurture their customer relationships.
This interview was originally published on June 14, 2020.
What is Omniconvert?
Omniconvert is a growth marketing platform. We aim to optimize the digital customer’s journey by using segmentation and data that most companies have, but don’t know how to use.
What data should companies be using, and what marketing decisions should they drive?
Most companies have a lot of transactional data but are obsessed with what is happening with their visitors instead of looking at their customers. Our approach is to grab their transactional data and the satisfaction of their current customers and use it to analyze customer habits, patterns, and voice. This data can improve their customer acquisition campaigns, their product buying teams, and of course, optimize the customer journey.
How does your Reveal product retain, acquire, and even bring customers back?
RFM is determined by your own scoring system of 1 – 5 based on criteria of how recently and frequently customers place orders as well as the total monetary value of those orders. For instance, you might give a customer who has purchased within the last 30 days a Recency score of 5/5. If they’ve placed more than ten orders, their Frequency rating is 5/5, and if they’ve spent $5,000USD, a Monetary value score of 5/5.
After segmenting your customers by RFM, you might see that 1% of your customers are your best customers and are generating around 20-25% of your revenue. You can use this data to identify the patterns of your ideal 5/5/5 customers – where they live, their age, and what makes them keep coming back and purchasing. Now instead of going to acquire customers you know nothing about, you’ll be able to look for and target only ideal customer profiles by using tools like the Facebook algorithm to find you a lookalike audience based on your 5/5/5 customers.
Once customers are segmented by RFM, what are some actions you might take?
Once segmented by RFM scores, you can handle each customer group differently according to your goals. For example, you can retain your true lovers, your best customers, by giving them personalized perks to thank them for being one of your VIP customers.
The way to reengage former customers is to ask questions to understand better the barriers that caused them to stop short of purchasing and fix them.
What other intelligence is available in Reveal?
With Reveal, you will be able to see the mathematical probability of a customer placing their next order. This helps ascertain how many orders a customer needs to place before purchasing from you becomes habit-forming. Let’s say your pattern is that after customers have placed three orders, the chance of them placing a fourth, fifth, sixth, etc. order is three times higher than after their first. Now you know to put a lot of energy into creating a relevant customer journey making sure they feel appreciated, so they come back and place three orders since, after that, the chances are much higher they will continue purchasing from you on autopilot.
What support is available for customers to help them understand their customer’s journey?
For the first three months, we help our customers with suggestions to create and understand their RFM segments so they could start activating ongoing campaigns. Additionally, we have agencies and business consultants who can advise and support our customers.
What are some of the tools or features within your Explore product that helps increase conversions?
Surveys are the most critical piece of conversion rate optimization because even if you have quantitative data from Google Analytics or another web analytics service if you don’t ask real questions of real users, you might be misled by the numbers.
That’s why surveys are an essential part of Omniconvert’s Explore to help understand what stops customers from converting, what stops them from adding products, what stops them from continuing the order journey.
What goes into creating a successful customer survey?
First of all, you should not make any assumptions about why your customers behave in a certain way. Start with an initial survey asking open questions like “What stopped you from completing your purchase?” and allow them a short paragraph for their response. Your response rate may not be that high, but you’ll get reliable answers and insights.
Once you understand that most of your customers are stopped by lack of trust, or by high prices or by your return policy, you can create a new survey asking the same question, but with answer options based on real data, rather than your assumptions.
What actions can you take on the survey results?
Based on the results from the surveys, you’ll be able to get to the next phase of your conversion rate optimization by combining your qualitative research with quantitative research. Let’s say the most significant drop in your funnel is at the cart page, and your survey shows that people have concerns about your return policy. You can now use the A/B testing feature of our Explore tool and create a second version of the cart page with an improved return policy and test it against your current cart page. By using quantitative research, qualitative research, and A/B testing, you can now make data-driven decisions on the things that need to change to improve the conversion rate.
What are some of the other tools in Explore that can help increase conversions?
Another tool in Explore is the overlays and pop-ups. I’m not a big fan of the usual pop-ups, but relevant pop-ups combining features like personalization or interactive content can persuade a customer to make a purchase.
For example, if you have a web site visitor from Louisiana and show a pop-up that says ‘Subscribe now to receive 5% discount’ overlay, that might not work. But if your pop-up says, “Subscribe now to receive a 5% discount and join our 242 happy customers in Louisiana.” the customers will be more favorable to you as a vendor feeling like you are focused on their region.
What type of web personalization can you gather to push out into a pop-up?
We use more than 40 data points to enrich a website and make it personal. The first web personalization I did was in 2011 at my former company, which sold car insurance. We displayed a different website depending on the car model selected by the visitor. Many men seem to have a relationship with their car, so when it comes to insuring it, we activated their attachment by using that personalization.
While we are one of the only platforms using 4th party data like GeoIP and even weather conditions, experience has shown us that the best kind of personalization is with 1st party data. The weather in his location isn’t relevant to an angry customer whose previous order was delayed. It’s more important that when he returns to your website, he feels cherished with a pop-up that says, “We’re sorry we dropped the ball last time <name>. This time we’ll make it better.” Using 1st party data like a customer’s satisfaction score, their lifetime value, or the last product purchased to personalize an overlay makes marketing more efficient.
What data is available to analyze and determine success?
Instead of looking at the last conversion as just the customer’s order, you can look at a lot of micro-conversions or events throughout their journey. So you can see that a customer clicked on the product page, zoomed in on the product image, looked at three more products, and on the cart page, filled in the first three fields. By tracking these kinds of micro-events on the Explore dashboard, you’ll be able to see if the B version with the updated return policy is better than the original A version. Now you will not only know IF you are selling more but also WHY.
What is Adapt?
Adapt is our new product, still in beta, which uses machine learning and automation to help companies grow.
For example, we see that when used properly, interactive content is very appealing and efficient. So, we’ve handcrafted the most successful interactive, personalized overlays and allowing machine learning to handle the process of pushing the right overlay with the right message at the right time to the right user.
Currently, A/B and personalization testing of things like changing a block of text, pushing a particular message, or adjusting the menu, needs to be done manually. With Adapt, you create all the overlays you want to test and let the system push the correct operation and measure its efficiency based on micro-conversions. So if the machine sees that overlay #42 performs best, it will be pushed further. Now you can grab revenue that was leaking when your website was static and delivering the same message to everyone.
Please tell us about your test case of targeted web personalization with Avon that increased the conversion rate of a category page by 96%.
When Avon noticed a low conversion rate in their makeup category, they sent surveys to their customers to determine what stopped them from completing their orders. One of the main reasons was customers were afraid that the makeup would not complement their eye color. Based on that finding, we crafted an experiment with an overlay that was triggered when customers went to the makeup category. The overlay simply asked the customer to select their eye color and, based on their selection, were directed to a specific category page with products that perfectly complement their eye color. Because of the framing effect and the subconscious cognitive bias of the customer that an expert from Avon selected those products, especially for them, the conversion rate increased by 96%.
Where do you see the conversion rate optimization industry going in the future?
Based on our understanding of the conversion rate optimization industry and a lot of customer interviews, I think it will transform into part of a broader category called Customer Journey Optimizations (CJO). Since we are living in an experience economy, we need to empower eCommerce managers to craft better customer journeys. We need to get rid of the product-centric mentality of pushing lots of products, discounts, and promotions at customers without cultivating any kind of personal relationship with them. Customer-centric businesses that understand, monitor, and nurture the relationships they have with their customers are the businesses that will thrive. So the future will belong not to the ones that are best at acquiring customers, but to the companies that are the best at retaining their customers by understanding their behavior and continuing to delight them.