As digitisation takes over the world, more and more people are becoming self-aware of the purchase choices they make. Online research has become a norm before any purchase decision, be it an insurance policy, gym membership, holiday booking or car purchase, 88% consumers go online before making a purchase 👩🏻💻.
While this statistic continues to boost the budgets for digital marketing, there has been a key characteristic shift in the consumer behavior i.e. expectation of personalization 🙋🏻♂️.
Personalized Sales vs Personalized Marketing
Personalization has been a topic of concern for digital marketers for the past decade. While sales has been a highly personalized activity for most companies (that need prospect generation and one-on-one sale), marketing has not been able to find scalable solutions for this need. Marketing typically runs at a scale of 100x to 1000x of sales. Personalizing the user experience at such a scale is not a straightforward task. Personalized ad delivery is extensively used in the digital domain, but once these ads do there job and leads are generated, businesses find it tough to keep the process personalized to a user. All the lead processing and lead qualification happen through automated filters and bulk processes. These processes typically lack the transparency to communicate what led to the individual user not passing through the funnel.
It often happens that users with the right intent and qualification get dropped out because their individual needs could not meet the process structure 😓.
Take for example the scenario of Ross, a call center employee.
He is thinking of getting a car and is looking for a car loan. He works night shift and sleeps during the day hours. He browsed for some loan options and chose CompanyA. Obviously, he had a few queries. He requested a callback but the sales agents of the CompanyA were offline. So, he spent some effort and noted his queries and wrote an email to the company. The next day, the sales agents called him during the regular working hours but he was asleep 😴. He did receive an email response, sharing some details but he had some followup queries. It was a busy week at office so he couldn’t do another round of long email and procrastinated replying to next followup emails. The process of the CompanyA marks a lead inactive after 3 follow-ups on email and call. Hence, Ross was marked inactive after 10 days 🚫.
CompanyA is no longer pursuing Ross because it incurs a cost to deploy resources for callbacks. Their average lead would take a decision in 10 days with all the followups but Ross is an exception in the process and there would be many other such exceptions. Given this scenario, there was no way for the company to track why Ross did not respond and that they lost a potential customer.
One can imagine many such scenarios where the need of process personalization or content personalization is eminent to boost the efficiency of the sales funnel.
Chatbots open up a unique dimension for the marketing world offering a practical solution to the personalization problem.
Chatbots – the perfect way of personalized marketing
🤖Chatbots are conversational automations, enabling a machine and a human to have a two-way interaction using text and media messages. For the past couple of years, chatbots have been designed to serve a variety of purposes. While the language understanding capacities of these bots have been limited, it has not stopped creative business people to find great utilities for conversational automation. Chatbots have seen adoption in all tiers of businesses with the simplest to the most complex implementations done and different levels.
Morph.ai is one of the very first and world’s leading chatbot builder platform. We focus on
Chatbots for Marketing and have developed a system tuned towards marrying marketing automation and conversational automation. We have designed our system with the goal of making marketing as personalized as sales. Given the challenges we discussed above, we created the system to achieve 3 things :
- Create a conversation design system usable by marketers
- Build a scalable system in sync with the marketing processes
- Add personalization capabilities like never before
We have extended our super-flexible and powerful chatbot builder tool to bring it in sync with the marketing processes of campaigns, lead generation, qualification, lead scoring, funnel optimization, lead query resolution etc.
To achieve the required personalization capabilities, we have created our machine learning engine
MARK - the chat marketing assistant. MARK manages each conversation like a real marketing assistant would. It checks each conversation and marks leads which look genuine and which do not. It schedules follow-ups prospects at a time that would suit the individual. It checks if the user is not willing to share some personal info and gives an option to skip for the time being. Many such little things give MARK the edge over regular marketing automations.
The magic we have done!💫
We have worked with more than 20 large brands and put this in action. Conversational lead generation has produced unparalleled results. Our typical gauge to measure the system performance would be the current best marketing campaigns of the brands. The bet has been that the conversational automation of Morph, coupled with the AI-powered MARK can do better than the best regular marketing campaigns of brands. Certainly, not all conversational campaigns could meet the strict benchmark, but most did very well. Maintaining the privacy of individual brands, we are publishing below the average results achieved across brands and a variety of associated dimensions.
|Lead Quality||Lead Capture||
- Avg. Improvement – Average among all campaigns of the percent improvement over the benchmark campaign of the brand.
- Conversion – Leads reaching the final stage of the brand funnel. Ratio over total leads qualified.
- Lead Quality – Leads sharing authentic key information, typically phone number or email address. Ratio over the total leads captured.
- Lead Capture – Ratio of visitors (website visitors or ad clicks as applicable) available to pursue by starting the chat.
- Engagement – Average of engagement rate (read/click/reply rate as applicable on every bulk message sent) on all messages sent to users.
Interested in some secrets?
We are compiling some in-depth insights into campaign performances, chat marketing strategies and the magic of MARK. Be the first one to get access to the exclusive report. Stay tuned.