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    Sell AI outcomes to enterprises, not tools, one post argues

    The post describes Pepper's Atlas as a 365-agent marketing system, with agents handling 80% of the work and a senior marketer on the customer's team responsible for results.

    GR
    1 Source, 24d ago, first seen 24d ago

    TLDR

    The post presents Pepper as an example of selling enterprise AI around results rather than tools. It says Pepper built Atlas using experience from running organic growth programs for more than 250 large enterprises. The system, as described, tracks buyer questions, publishes pages designed to answer them, earns mentions across sources AI systems trust and attributes the leads that follow. The post says Pepper sells organic and AI search-sourced sales pipeline as a single line item, with a commercial model that holds the company accountable for the customer's result.

    Combined views

    190.3K

    1 Source, first seen 24d ago

    Combined views

    190.3K

    1 Source, first seen 24d ago

    547 likes
    547 likes
    52 comments
    954 saves
    40 reposts

    Sentiment

    Positive——Negative

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    52 comments
    954 saves
    40 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    1 Source

    @gokulrOutcome-based Marketing To sell AI to enterprises, you need to sell Outcomes For 20 years, software companies sold tools to enterprises. Today, the best and fastest growing companies sell outcomes, not tools. @pepper_content is doing this for marketing. Pepper got its start running organic growth programs for more than 250 large enterprises. The team was responsible for monthly results, so it learned the work in detail and documented every step. Pepper used that experience to build Atlas, a system of 365 agents. Atlas tracks the questions buyers ask, publishes pages designed to answer them, earns mentions across sources AI systems trust, and attributes the leads that follow. Agents handle 80% of the work. A senior marketer on the customer’s team owns the number. Pepper sells organic and AI search-sourced pipeline as a single line item. Its commercial model puts the company on the hook for the customer’s result. That accountability matters. AI-native services depend on detailed knowledge of the work: which decisions recur, where judgment is required, and which actions produce results. Pepper accumulated that knowledge by serving customers for years. It then encoded those decisions into software while keeping a person responsible for the KPI. @SinglaAnirudh started Pepper at 18. He has spent every year since learning what CMOs need and building the company around those needs. Building a services company is hard. Automating most of its work while remaining accountable for customer results is harder. Pepper is showing what an outcome-based AI company can look like. I’m excited to support them on this journey.

    1 Source

    @gokulrOutcome-based Marketing To sell AI to enterprises, you need to sell Outcomes For 20 years, software companies sold tools to enterprises. Today, the best and fastest growing companies sell outcomes, not tools. @pepper_content is doing this for marketing. Pepper got its start running organic growth programs for more than 250 large enterprises. The team was responsible for monthly results, so it learned the work in detail and documented every step. Pepper used that experience to build Atlas, a system of 365 agents. Atlas tracks the questions buyers ask, publishes pages designed to answer them, earns mentions across sources AI systems trust, and attributes the leads that follow. Agents handle 80% of the work. A senior marketer on the customer’s team owns the number. Pepper sells organic and AI search-sourced pipeline as a single line item. Its commercial model puts the company on the hook for the customer’s result. That accountability matters. AI-native services depend on detailed knowledge of the work: which decisions recur, where judgment is required, and which actions produce results. Pepper accumulated that knowledge by serving customers for years. It then encoded those decisions into software while keeping a person responsible for the KPI. @SinglaAnirudh started Pepper at 18. He has spent every year since learning what CMOs need and building the company around those needs. Building a services company is hard. Automating most of its work while remaining accountable for customer results is harder. Pepper is showing what an outcome-based AI company can look like. I’m excited to support them on this journey.