AI for business

Through DigiBlender AI, my AI advisory practice, I help small and midsize businesses cut costs, get rid of repetitive clerical work, and turn the data they already have into measurable revenue. The work falls into six services.

AI strategy

Where can AI actually help your business?

Most owners are tired of consultants pitching six-month theoretical roadmaps. I find the two or three operational bottlenecks costing you the most time and payroll right now.

• AI opportunity assessment
• Workflow friction analysis
• AI readiness and data hygiene
• Tool selection: build or buy

What you get: a 90-day implementation roadmap ranked by ROI, with software cost projections, data privacy classifications and the hours each step should give back.

Delivered through the AI Opportunity & Readiness Audit (see the tiers below).

AI automation

Stop doing repetitive work by hand.

Retyping data between your inbox, CRM, spreadsheets and other software becomes an automated pipeline, with validation at every step and a person reviewing anything uncertain.

• Lead intake and qualification
• Customer inquiries and triage
• Document and PDF extraction
• Automated reporting and alerts
• Data sync between systems
• Internal knowledge agents

Safeguards: every workflow has validation checkpoints, error fallbacks, and 14 days of hands-on tuning after launch, so your staff stay confident and in control.

Delivered through a Rapid Implementation Sprint.

AI marketing

Use AI to make marketing smarter.

This builds on 20 years of national analytics and optimization work at TBWA (Visa, KPMG, Gatorade), Disney and Universal. AI replaces guesswork with dynamic targeting, fast creative testing and automated attribution.

• Customer segmentation: cohorts that update with purchase behaviour
• Campaign and ad analysis: spotting creative fatigue early and optimizing ROAS
• Content and SEO: scaling content with human review, without losing your brand voice
• Lead scoring and routing: getting high-intent buyers to sales first
• Marketing automation: lifecycle emails, personalized offers and re-engagement
• Competitive intelligence: tracking competitors’ pricing, offers and search share automatically

Measured in revenue: it shows which creative and which audiences bring in profitable, paying customers, so ad budget stops going to the ones that don’t. The goal is higher ROAS, lower acquisition cost and faster sales cycles.

AI + analytics

Turn the data you already have into decisions.

This is where my analytics background matters most. I connect your separate systems (GA4, Shopify or your e-commerce platform, CRM, ad platforms and sales data) into one warehouse, then use AI to answer leadership’s questions on demand:

• Why did sales drop last month?
• Which customers are worth the most over their lifetime?
• Where are we losing conversions in the funnel?
• Which channels bring in profitable customers?

The ready-made version of this is DigiBlender’s automated marketing data pipeline. See also AI-powered analytics.

Predictive analytics

From “what happened?” to “what will happen, and what should we do?”

Prediction is its own discipline, not a feature buried in generic AI. It lets you anticipate demand, cash flow and churn before you spend. I work with six models:

1. Revenue forecasting: cash flow and inventory over time
2. Conversion prediction: purchase intent from session behaviour
3. Customer lifetime value: multi-year margin, projected within 14 days
4. Churn and replenishment: 14 to 30 days’ warning before loyal customers lapse
5. Campaign performance: ROAS by day three, so budget can move early
6. Predictive lead scoring: identifying high-value deals

The models are deliberately lightweight: they reach statistical confidence on small and midsize business data volumes without an enterprise data science team.

AI training

Teach your team to use AI well.

No generic ChatGPT theory. I train staff on their own daily workflows, so the tools actually get used and company data stays confidential.

• AI fundamentals for staff
• Prompting and context design
• Workflow design and delegating tasks to AI
• Choosing and connecting tools
• Data privacy and contract opt-outs
• Workshops for specific departments

Governance included: a practical one- to two-page company AI policy that sets clear limits on public tools and keeps client and customer data out of model training.

Included in Implementation Sprints and the advisory retainer.

Three ways to work together

Every engagement is a fixed fee or a clear monthly tier. There is no open-ended hourly billing.

1. AI Opportunity & Readiness Audit

10–14 days · $1,500 fixed fee. A paid diagnostic that maps your highest-return automation opportunities before you commit to anything bigger. The fee is fully credited toward a Sprint if you go ahead within 14 days.

• A 90-minute executive session on friction, retyping and admin bottlenecks
• A map of your current systems and workflows: intake, documents and CRM handoffs
• A data security and privacy review, including unapproved AI use and customer data
• A prioritized 90-day roadmap with projected ROI
• A 45-minute walkthrough with your leadership team

2. Rapid Implementation Sprint

3–4 weeks · $5,000 fixed fee ($3,500 with the audit fee credited). One automated pipeline, live, for one approved bottleneck such as intake, document extraction or an internal knowledge agent.

• An architecture blueprint: data flow, webhooks and error handling
• One live workflow
• Validation checks with human review
• Staff procedures and video training
• 14 days of daily monitoring and tuning after launch

3. Fractional Chief AI Officer

3-month minimum · $2,000 a month, including one new workflow sprint each quarter. An ongoing advisory partner, limited to six clients.

• Advisory sessions every two weeks: bottleneck reviews and new tools worth adopting
• Monthly maintenance: prompt tuning, model upgrades and error monitoring
• One new pipeline every 90 days
• Vendor contract review and privacy governance
• Priority async access with a 24-hour response

Not included: advisory covers strategy, architecture, tool selection and governance, not hands-on building. If a use case needs custom automation (Make or Zapier connections, or custom API scripts), it’s scoped separately: I either guide your team through the build or bring in vetted freelance specialists under my architectural review.

Not sure where to start?

Start with the 10–14 day audit. I review your current tools, find the friction and lay out the order to tackle it in. Book the AI audit on DigiBlender AI, or send me a message.