“Today brands have to be more cautious and attractive in all interactions they have with the user.”
Graduated in Computer sciences and Systems Engineering, Rui Campos entered the job market “in the middle of the dot-com bubble”, when very little knowledge existed about digital audiences. Today, Rui is CEO of Smarkio and is proud of the marketing automation technology he helped build and which helps European customers process more than 20 million emails and more than 150,000 chatbot conversations across multiple channels each month. We asked Rui to share his strategic vision on audiences and conversion.
What are the main challenges in audience segmentation today?
In my opinion, the main challenges of managing and segmenting audiences are four:
- Combining information from different sources, creating a unique view of each user that allows us to improve segmentation – the Customer Record;
- Manage data collection – GDPR and regulation around cookies constrain data collection, and brands have less access to profile enrichment information obtained through third-party partners;
- Combine online with offline, synchronizing the two worlds to improve Customer Record and improve segmentation;
- Test, test, test – a lot of information, determining which parameters or segments lead to the best conversion rates, requires a constant job of measurement and a lot of testing.
What impact has GDPR had on how we segment our audiences?
There are two broad areas of impact of GDPR in the way audiences are segmented:
- Information Collection – GDPR requires explicit user consent to data collection. Onboarding flows can be developed to make registration and consent more appealing.
- Mechanisms for removing consent and the right to be forgotten – brands today have to be more cautious and attractive in all interactions they make with audiences, preventing the user from leaving the conversion flow and, consequently, the audience.
Is it possible to segment an audience that already exists? How?
Yes, through the use of Marketing Automation plans that test the audience’s receptiveness to certain interests (by sending emails, SMS or website personalization) and updating each user’s Customer Record according to the interest shown.
What is the role of chatbots in lead segmentation?
Chatbots benefit from greater user receptivity compared to traditional lead qualification forms: they are conversational and adapted to mobile. For example, one of our customers replaced a multi-question form with a chatbot and more than doubled their conversion rate for qualified leads.
Do chatbots work best on their own or are there advantages in combining chatbots with a human service?
It depends on the purpose and context of the chatbot. In customer service operations, there are advantages in having the ability to transfer to a human service in situations that the chatbot cannot resolve. But there are important points to watch out for:
- Transparent transition – although the user should be able to distinguish when talking to an automated chatbot or a human, this transition should be as simple and smooth as possible;
- Context – it is important to ensure that the human agent has all the context of the conversation held with the chatbot, to avoid the user having to repeat himself;
- Availability – Chatbots have the advantage of working 24x7x365. In situations where it is not possible to guarantee human assistance on the same scale, alternatives must be given;
- Scalability – Related to the point of availability, an automatic chatbot can “serve” hundreds or thousands of users simultaneously, which usually does not mean the same availability of human assistance. This forces us to create alternative channels when human service is not available.
What opportunities do you think will arise for managing digital audiences?
Conversational interfaces are constantly evolving and the level of innovation in these areas is very fast. I would say that we will have opportunities in four areas:
- Channels – In addition to the Web, new communication channels have appeared in the world of chatbots, such as WhatsApp, Facebook Messenger and Instagram. It’s about finding users where they are;
- Artificial Intelligence – Natural language processing (NLP) capabilities have evolved a lot – in addition to capturing intentions, they interpret parts of text. For example, when I write “I want to get last month’s invoice”, the system detects that my intention is to download the invoice and automatically selects the month before the current month. The evolution in NLG (Natural Language Generation) and new deep learning algorithms will increasingly improve chatbots;
- Voice – With the proliferation of voice assistants (Siri, Amazon Alexa, Google Assistant) voice bots will gain more and more relevance;
- Automation – The combination of chatbots with automation tools and RPA (Robotic Process Automation) allow improved multichannel interaction and trigger complex automation processes of qualification and management of users – hyper-automation.
Together, these evolutions will increasingly allow brands to interact with their audiences more frequently and in different channels (omni-channel), obtaining greater knowledge about their users and audiences.