Outbound 2.0: AI Redefines the Workflow
Let's delve into the evolution of outbound from "Before AI" to the "Post AI" era, challenges with current AI tools and workflows and how can you solve these challenges and get powerful results.
Hey, Welcome to this week’s edition of “Future of Prospecting” Newsletter by “Evabot”.
We have been researching Generative AI Technology for the last 18 months and have been astounded by the use cases it brings in Prospecting through Hyper Targeting and Personalisation. For Sales leaders and Revenue leaders, the main challenge with AI-led Prospecting is “How and What not?”
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Quick Question…
Have you scaled your outbound process?
Or
Are you planning to scale your outbound process?
In this newsletter, we’re going to share potential challenges associated with scaling outbound processes, and how you can adapt Outbound 2.0 with fail-proof strategies.
How are teams scaling their outbound?
Sales leaders are fully committing to expanding their outbound engine to achieve consistent sales results. Below are the steps they are currently implementing, along with the development workflows that utilizes various AI tools:
Before AI
After AI
Step 1 - Building the Account List
Example: Focusing on sales leaders in San Francisco from companies with over 200 employees, those who have recently changed jobs, and companies that have experienced a 30% growth in the last year.
Work Items:
- Identify key decision-makers and high-potential companies for targeted outreach.
- Regularly update and refine the account list based on changing market dynamics.
Step 2 - Enriching Account Details Using AI
Example: Enhancing account profiles with recent job transitions, industry insights, and mutual connections.
Work Items:
- Use an AI tool with verified and accurate data.
- Continuously monitor the effectiveness of enriched data in improving response rates and conversions.
- Implement personalized and omni-channel outreach strategies based on enriched account details.
Step 3 - Tracking Intent Data and Insights (Regularly update)
Example: Monitoring website visits, email interactions, and content downloads to gauge prospect interest and using AI to look for signals from news, social media, job changes, announcements, etc.
Work Items:
- Use intent data to tailor follow-up strategies and provide value-added interactions.
- Analyze intent data metrics to refine outreach approaches and improve engagement rates.
Step 4 - Sending Personalized Emails Using AI
Example: Crafting tailored emails that highlight how the solution addresses specific pain points for individual prospects.
Work Items:
- Align email content with the recipient's business to increase relevance.
- Track email open rates, click-through rates, and responses to optimize email personalization strategies.
Step 5 - Using Power Dialers for Cold Calling
Example: Implementing power dialers to automate and streamline the outbound calling process, allowing sales reps to make a higher volume of calls in less time.
Work Items:
- Enhance productivity and call efficiency by reducing manual dialing.
- Track key metrics such as call connect rates, conversation quality, and lead conversion rates.
Step 6 - Automating Follow-Ups Through LinkedIn and Emails
Example: Setting up automated sequences for follow-up messages to maintain consistent engagement.
Work Items:
- Set up follow-up sequences to ensure timely and relevant interactions with prospects.
- Evaluate the effectiveness of automated follow-ups in nurturing leads and driving conversions.
Challenges and how we are using AI to solve them
However, there are significant pitfalls associated with the current methods of scaling an outbound engine. Many of these challenges stem from an increased reliance on AI for tasks that were previously managed by SDRs or AEs.
Challenge 1 - Having a comprehensive account list and reaching out in a random order
Efforts may be wasted if companies in the list don't require your offering. Failing to target companies with pressing needs can result in missed opportunities.
Solution
Prioritize accounts based on pre-intent signals so that you won’t miss an opportunity:
- Utilize an AI tool to prioritize accounts using recent signals from 10K Reports, quarterly filings, news, social media, and interviews.
- Understand the logic behind prioritization to ensure your outreach targets prospects experiencing pain points effectively.
Challenge 2 - Too many signals and insights to use
Disinterest from prospects may arise when using irrelevant insights, while missed opportunities can occur due to human errors in signal interpretation and prioritization.
Solution
Prioritize signals for each account based on context so that you will get the attention:
- Develop a workflow to align signals and insights with your product or service context for more relevant outreach.
- Ensure that the prioritized signals enhance the outreach without coming across as overly sales-oriented.
Challenge 3 - Generic personalization in scaled outreach efforts
Sending generic messages with cross mixing benefits and business goals may not stand out. Impersonal and verbose emails with repetitive patterns may fail to capture prospects' interest.
Solution
Sharply personalize outreach using expert frameworks and high-priority signals to get a response:
- Implement a workflow where SDRs can select templates created by experts for higher response rates.
- Integrate high-preference account insights and expert templates (ex - OPPS, PSA etc. ) using AI to craft personalized and compelling messages.
Challenge 4 - Using generic discovery questions in cold calls
Common openers and sales pitches can lead to prospect disinterest. Lack of interest (prior research to capture attention) and relationship-building in initial calls do hinder conversion rates.
Solution
Conduct cold calls efficiently with power dialers and call-prep insights to improve calling conversion rates:
- Create a workflow that converts account insights into contextual call prep notes for SDRs to have relevant information at their fingertips during calls.
- Equip SDRs with call-prep notes including pain points, recent news, CEO points, and insights from 10K reports for more engaging conversations.
Challenge 5 - Using redundant or outdated insights in engagement efforts
Utilizing irrelevant or outdated insights may lead prospects to view the communication as spam. Negative impact on trust and relationship-building with prospects.
Solution
Periodically update and prioritize account insights:
- Establish a workflow to periodically prioritize the account list based on priority order and score account insights for confidence levels.
- Ensure that account insights are regularly updated for recency and relevance to maintain effective outreach strategies.
- Use a tool that provides insight sources and reasoning to validate relevance and accuracy.
- Offer feedback to the system and highlight any irrelevant insights for improvement and reporting to the customer success team.
Scaling outbound - The Right Way
It involves strategic account prioritization, personalized outreach, and leveraging insights effectively to drive engagement and conversions.This comprehensive approach should be a core part of your workflows to mitigate any potential setbacks.
Start by identifying pre-intent signals to prioritize accounts and ensure no opportunity slips through the cracks. Contextualize these signals for each account to capture attention effectively. Utilize expert frameworks and high-priority signals for sharply personalized outreach that elicits responses. Employ power dialers and prepare with insightful call strategies to boost cold calling conversion rates. Maintain the precision and relevance of your account insights consistently, and make it a routine to update and re-prioritize these insights.
By implementing these strategies and workflows, you can enhance your outbound scaling efforts to drive better engagement and conversions in your sales process…
Curious to know which tool to use for all this? Try Evabot…
Evabot can help you scale your outbound right !!
With Evabot, you can seamlessly scale:
- Account Prioritization and Pre-Intent Signals: Easily identify potential leads through analysis of 10K Reports, Earnings Calls, News, Social Media, and Interviews. This allows you to prioritize accounts that show signs of needing your solutions before they even start the search.
- Message Building for Email and LinkedIn Outreach: Craft personalized outreach messages for Email and LinkedIn by utilizing pre-intent signals, expert frameworks, and the specific business context of your targets. This approach ensures your messages are both relevant and engaging.
- Cold Calling Processes: Enhance your cold calling outcomes with account insights and contextual discovery questions, integrated into automated call-prep data. This "Call-Prep 2.0" feature equips your team with the information they need for more meaningful and productive conversations.
In short, are you looking for help on
→ Personalized and Hyper-targeted messaging at scale?
→ Call-Prep Notes at scale?
→ Account Prioritization data and Pre-Intent Signals for 1000+ accounts?
Evabot plugs into your existing scaling process in one of the following ways:
Account Prioritization at Scale
Account list → Prioritization (with frequency) → Prioritized account list for outreach
Account Prioritization and Insights at Scale
Account list → Prioritization (with frequency) → Account insights (updated confidence scores periodically with sources) → Checked for precision, relevance and accuracy (i.e. time checks, hallucination checks, and context checks) → Account list (with order) with insights (confidence scores) to use
Call-Prep at Scale (for 1000+ accounts)
Account list → Prioritization (with frequency) → Account insights (updated confidence scores periodically with sources) → Checked for precision, relevance and accuracy (i.e. time checks, hallucination checks, and context checks) → Account list (with order) with insights moved to call-prep notes (Ex- in Outreach) for each account
Personalized and Hyper-targeted messaging at scale
Account list → Prioritisation (with frequency) → Account insights (updated confidence scores periodically with sources) → Checked for precision, relevance and accuracy (i.e. time checks, hallucination checks, and context checks) → Account list (with order) with insights and pre-intent signals for personalisation → Personalized Message building (through AI) with option to choose from expert frameworks and relevant insights → Directly bulk sending through your messaging tool (Ex - Outreach)
Now, you have all the failure cases to address, tips and techniques to implement, and tools to achieve your sales quota…
How are you planning to fail-proof your outbound scaling efforts?
Want to see how we can actually help scaling your outbound engine with AI?