IMPRINT AIM™ AI Mapping Method

imprint AIM™

AI mapping method

Artificial Intelligence (AI) is everywhere. In the business world, seventy-seven percent of companies are either using or exploring the use of AI, according to National University.

Top Benefits Achieved Through Generative AI Initiatives

AI initiatives have: 33% improved efficiency 12% improved innovation 10% improved existing products and services
Whether you’re not sure what AI can do for your business, unclear about where or how to test or are just overwhelmed by the number of AI solutions to navigate, you’re not alone. That’s why we created Imprint AIM™.

Imprint AIM’s
3-step Approach

Imprint AIM™ takes a three-step approach to help you define goals, pilot AI technology, and scale Generative AI (GenAI) solutions in your organization.

1. Define goals

    • Define business goals and objectives for AI to support
    • Align with broader business strategy and marketing goals
    • Educate decision-makers on current AI capabilities to inform goal-setting and vision.
    • Prioritize the most impactful opportunities

2. Identify pilot test cases

    • Identify and implement pilot use cases
    • Test and learn
    • Gather data, incorporate insights,  and report on preliminary results
    • Address stakeholder concerns

3. Build a framework for use and scale

    • Balance potential benefits, costs, risks, and alignment with strategic direction.
    • Articulate value propositions for using GenAI
    • Codify framework for ongoing GenAI use

Defining marketing goals

Below we provide examples of marketing goals where AI might help:

Journey Mapping

    • Reveal needs and desires based on data about e.g., past transactions, service inquiries, investments held, risk tolerance, strategic goals
    • Anticipate evolving needs, track sentiment, detect pain points
    • Build 1:1 relationships at scale
    • Infer client needs through data, communications, and offerings
    • A granular view of the journey that’s unobtainable other than through AI

Brand Awareness and Trust

    • Customer Intelligence: refine branding, messaging, and experience based on AI analytics
    • Sentiment Analysis: respond to trends, themes, and changes via AI data on public commentary
    • Personalized Content: highly personal content creates more value, delivers more relevancy, and thus builds trust

Content Creation

    • Brainstorming ideas
    • Developing outlines
    • Versioning for different audiences
    • Creating summaries, abstracts from originals
    • Application of editorial standards
    • Creating promotional assets from original piece
    • Personalized content for in situ/contextual digital experiences

Client Acquisition & Growth

    • Driving growth
    • Reducing churn
    • Converting leads
    • Ensuring data, technology, and processes are in place
    • Identifying and managing gaps
    • Measuring incremental lifts
    • Product uptake
    • Campaign efficiency
    • Customer lifetime value
    • Demonstrating ROI based on pipelines or flows vs. historical performance.

Loyalty & Advocacy

    • Personalization: tailor comms, content, offers and cross-sells based on preferences or journey stage
    • Sentiment Tracking: analyze behaviors and feedback to identify then proactively address pain points
    • Predicting Churn: use transaction data, engagement metrics, complaints etc. to identify those most likely to churn and deliver retention offers or messaging

defining the test pilot 

For the pilot test-case phase, it can be helpful to see examples of the types of questions we ask:

Creation

    • VISION: How might these AI capabilities impact our strategy?
    • BENEFITS: What new opportunities and capabilities will it present
    • ADOPTION: How will our team/customers react to its use?

 Management

    • PROCESSES: Which ones will we need to transform or create?
    • SYSTEMS: How can we train AI to use our existing systems?
    • SKILLS: What skills are needed to use this tool and iterate with it?

Governance

    • PROTECTION: How do we safeguard our data?
    • RESPONSIBILITY: Who’s accountable for AI’s output? How do you review it?
    • COMPLIANCE: What disclosures do we need to make? To whom?

designing a framework

Following the successful pilot use cases, you will want to implement a series of guiding principles to inform all uses of GenAI.

1. What is our organizational risk tolerance for the use of GenAI?

2. What controls or restrictions should we put in place to manage those risks?

    • How might those controls differ for publicly available applications vs. proprietary GenAI models created specifically for our business?

3. Who makes the decisions about using GenAI within our organization?

4. What info do we need to share and with whom about our use of GenAI , both internally and externally?

take your ai efforts to the next level 

Imprint AIM™ can help you organization adopt and implement artificial intelligence in accordance with your timeline. Contact us to learn more about how Imprint’s expertise can expedite your AI initiatives.