Boosting Lead Generation with a Funnel-Driven Strategy: Harnessing the Power of Messenger Bots | Livio Marcheschi
Introduction:
When it comes to improving the performance of a Messenger bot designed for customer acquisition, one important concept to remember is the need for consistent ad-to-bot experiences. The ad and the bot should be created together, as a mismatch can result in poor traffic and low engagement. In order to understand why this happens, it’s crucial to conduct UX tests and gather feedback from users. Once you have a clear understanding of the issues, you can focus on optimizing different aspects of the funnel. This includes optimizing acquisition KPIs by using the Messages objective campaigns, targeting the right audience, and using low effort call-to-action (CTA) buttons. Additionally, optimizing activation KPIs involves ensuring that the welcome message is consistent with the ad content and using low effort questions to encourage engagement. Lastly, optimizing conversion KPIs involves building trust with users by asking relevant questions, explaining the purpose of collecting personal information, and providing incentives for users to leave their details.
Full Article: Boosting Lead Generation with a Funnel-Driven Strategy: Harnessing the Power of Messenger Bots | Livio Marcheschi
How to Improve KPIs for Messenger Bots: A Step-by-Step Guide
When it comes to creating and optimizing a Messenger bot for customer acquisition purposes, there is one important concept to keep in mind: creating consistent ad-to-bot experiences. In other words, the ad and the bot need to be conceived together in order to achieve optimal results.
At the outset, it is crucial to ensure that the ad and the bot are aligned in order to avoid poor traffic and low conversion rates. This was a lesson learned through real-world testing, where a low welcome message conversion rate signaled a disconnect between the ad and the bot.
To understand the reasons behind this disconnect, multiple UX tests were conducted with the bots, asking users to go through the entire funnel and provide feedback on their expectations at each step. It became clear that the main reason for drop-offs was that the chat experience did not align with the user’s expectations, which was attributed to different individuals handling the ad creation and bot development.
As a result, it was determined that the entire funnel needed to be considered together, starting from the ad. This led to the development of ads that were designed in conjunction with the bot using specialized ad mockup tools.
Now, let’s delve into the details of how to improve the different steps of the funnel, starting with the acquisition key performance indicator (KPI).
1. Optimizing the Acquisition KPI: Cost per Click (CPC)
To improve CPC, ask yourself the following questions:
– Are you using Messages objective campaigns for optimization at the campaign level? In tests, these campaigns consistently outperformed other types, including conversion campaigns.
– Are you targeting the right audience at the ad set level? Audience targeting has a significant impact on ad performance, just like in any other type of Facebook campaign. Consider creating lookalike audiences based on conversations already collected, as this has proven to be successful.
– Are you using a low-effort call-to-action (CTA) at the ad level? In tests, CTAs that required high user effort (e.g., “Send message”) performed worse than those with low effort (e.g., “Learn more”).
2. Optimizing the Activation KPI: Welcome Message Conversion Rate
To improve the welcome message conversion rate, consider the following questions:
– Is your welcome message content consistent with the ad text and image? As mentioned earlier, aligning the content of the ad with the welcome message is vital to ensure a seamless user experience.
– Are you asking a low-effort question? The purpose of the welcome message is to encourage the user to engage with the bot. To minimize friction, use low-effort asks, such as rhetorical questions like “Do you want to start?” or “Do you want to receive a free coupon code?”.
3. Optimizing the Conversion KPI: Lead Conversion Rate
Since the concept of a lead can vary from company to company, it is difficult to provide specific recommendations for optimizing this KPI. However, consider the following questions:
– Is the conversation building enough trust for the user to leave their contact details? In tests, it was discovered that shorter bots did not perform as well as expected. Users actually expected more questions before they felt comfortable providing their personal information. This suggests that building trust through relevant questions is essential for lead generation bots.
– Are you explaining why you are asking for personal information? To increase the likelihood of users providing their contact details, it is important to explain the purpose behind collecting such information and what will happen next. This includes when they will be contacted, by whom, and for what reason.
– Are you providing any incentives? Offering incentives for users to share their personal details, such as a free quote, sample, or high-quality content, can increase conversion rates. Encourage users with incentives in the ad and emphasize them in the welcome message.
By addressing these key questions and taking appropriate actions, you can improve the performance of your Messenger bot and achieve better KPIs throughout the customer acquisition funnel. Remember, creating consistent ad-to-bot experiences is the foundation for success in this realm.
Summary: Boosting Lead Generation with a Funnel-Driven Strategy: Harnessing the Power of Messenger Bots | Livio Marcheschi
When creating and optimizing a Messenger bot for customer acquisition, it is important to create consistent ad-to-bot experiences. The ad and the bot should be conceived together to ensure a seamless user experience. To improve the acquisition key performance indicator (KPI), you should consider using messages objective campaigns, targeting the right audience, and using a low effort call-to-action. For optimizing the activation KPI, ensure that the welcome message content is consistent with the ad, and ask low effort questions to minimize friction. To optimize the conversion KPI, focus on building trust with users through asking relevant questions, explaining the reason for asking personal information, and providing incentives.
Frequently Asked Questions:
Q1: What is Artificial Intelligence (AI)?
A1: Artificial Intelligence, commonly known as AI, refers to the simulation of human intelligence in machines that are designed to mimic certain cognitive processes such as learning, problem-solving, reasoning, and decision-making. AI enables machines to perceive, comprehend, and respond to their environment, allowing them to perform specific tasks without explicit programming.
Q2: How does Artificial Intelligence work?
A2: Artificial Intelligence works by utilizing algorithms and data to enable machines to learn from experience and perform tasks autonomously. AI systems are typically built using machine learning techniques, where algorithms analyze and derive insights from large datasets to improve their performance over time. These algorithms can be further categorized into supervised learning, unsupervised learning, and reinforcement learning, depending on the nature of the task at hand.
Q3: What are the different types of Artificial Intelligence?
A3: Artificial Intelligence can be classified into three main types: Narrow AI, General AI, and Superintelligent AI. Narrow AI, also known as Weak AI, is designed to perform specific tasks and excel within a limited domain. General AI, on the other hand, aims to possess human-like intelligence and the ability to understand and perform any intellectual task that a human can do. Superintelligent AI refers to AI systems that surpass human intelligence and possess enhanced cognitive capabilities.
Q4: What are the real-world applications of Artificial Intelligence?
A4: Artificial Intelligence has numerous real-world applications across various industries. Some key areas where AI is commonly used include:
1. Healthcare: AI can assist in diagnosing diseases, analyzing medical images, creating treatment plans, and improving patient care.
2. Finance: AI enables fraud detection, algorithmic trading, risk assessment, and personalized financial advisory services.
3. Transportation: AI is utilized in autonomous vehicles, route optimization, traffic prediction, and demand management.
4. Customer Service: AI-powered chatbots and virtual assistants are used to provide personalized and efficient customer support.
5. Manufacturing: AI optimizes production processes, predicts maintenance needs, and enhances quality control.
Q5: What are the possible implications of Artificial Intelligence on society?
A5: Artificial Intelligence presents both opportunities and challenges for society. While AI has the potential to revolutionize industries, boost efficiency, and improve our overall quality of life, it also raises concerns such as job displacement, privacy issues, biases in AI algorithms, and ethical considerations surrounding AI decision-making. It is important to carefully navigate the ethical and regulatory frameworks to ensure the responsible development and deployment of AI systems for the benefit of humanity.
