Business Context is where you teach Dalil AI the specifics of your company so that its insights, scoring, and tips are more relevant to your real sales environment. By filling out this section, you help the AI make better decisions, provide sharper recommendations, and adapt to the way your business actually works.

Think of it as giving Dalil AI a map of your business landscape: the industries you serve, how you sell, who your ideal customers are, and what makes you win deals. The richer the context, the more accurate and actionable the AI becomes.

What you can configure in Business Context

Dalil AI gives administrators a structured set of fields to describe their business. Each one feeds into the AI’s reasoning engine:

1. Basic company details

   • Name, website, and LinkedIn profile.

   • Used to identify your organization in AI responses and cross-reference online signals.

2. Industry and offering

   • Explain which industry you operate in and the products or services you provide.

   • Example: “We provide logistics software for last-mile delivery companies.”

3. Deal metrics

   • Average deal size (in USD, EUR, etc.)

   • Typical sales cycle length (e.g. 6 weeks, 7 months).

   • These values calibrate the AI’s scoring models: a $1M deal requires a different priority signal than a $1K one.

4. Sales process description

   • Describe your typical pipeline stages.

   • Example: “We use two pipelines: Sales and Customer Success. Sales has 6 stages from lead to closed won. Customer Success tracks upsell opportunities.”

5. Ideal customer profile (ICP)

   • Define who you sell to, including traits that signal a strong lead.

   • Example: “B2B SaaS companies with 20–200 reps, primarily in EMEA, that manage outbound sales on WhatsApp.”

6. Competitors and positioning

   • Add key competitor websites.

   • Describe how you differentiate.

   • Example: “Unlike Hubspot, we’re WhatsApp-native and mobile-first.”

7. Key data fields

   • Select which record fields matter most for analysis (e.g. ARR, employees, industry, LinkedIn, Dalil Score).

   • This ensures the AI highlights the right dimensions when producing signals or tips.

Why it matters

• Sharper scoring and signals: The AI can prioritize deals based on your real cycle length and ICP, not generic assumptions.

• More relevant tips: When suggesting a task, email draft, or pipeline update, the AI considers your industry context and deal metrics.

• Better insights: Competitive positioning helps Dalil AI generate smarter recommendations, like why to prioritize one lead over another.

Without Business Context, Dalil AI still works — but with context, its recommendations move from generic to tailored.

Best practices for filling it out

• Be specific, not generic: Instead of “We sell software,” write “We sell AI-powered CRM for SMBs in logistics and real estate.”

• Keep numbers realistic: Don’t overstate your average deal size or cycle length, as this distorts AI scoring.

• Update regularly: As your sales process evolves, revisit the context so AI always works with fresh information.

Example in action

• A company sets its average deal size at $50K and cycle length at 3 months.

• When an opportunity has been open for 6 months without progress, Dalil AI will flag it as stalled and suggest a next step (e.g. drafting a re-engagement email).

• If the ICP is defined as “B2B service providers with 10–50 employees,” and a lead fits this perfectly, the Dalil Score will increase accordingly.

How it connects with scoring and tips

Business Context directly powers the Dalil Brain.

• Signals (positive or negative) are calculated relative to your context.

• Tips are generated with actionable suggestions (create a task, draft an email, schedule a meeting, update a record) that align with your ICP, sales cycle, and competitor landscape.