Number of Seats/Users: daisee offers discounts based on the number of users or seats. A higher volume typically leads to a better discount structure, especially for enterprise-level usage.

Commitment to a Long-Term Contract: Discounts are often provided to companies that commit to using the service for a longer period (e.g., 1-year or 3-year contracts). A longer commitment shows daisee that the company is serious and willing to invest in the platform long-term.

No Active Discounts: Companies that are not already receiving other active discounts may have a better chance of qualifying for additional discounts from daisee. daisee reserves discounts for new customers or those not currently under promotional pricing.

Volume or Usage Commitment: daisee offers discounts if you agree to a minimum amount of usage or transaction volume. This could be based on data storage, transactions, or other metrics tied to how much you will use the platform.

Enterprise-Level Negotiation: Companies that qualify as “enterprise” due to their size or complexity (e.g., having large teams, multiple departments, or geographical presence) may be eligible for additional discounts from daisee. Such companies are often in a position to negotiate for better pricing.

Early Renewal or Prepayment: daisee often offers discounts if you renew early or prepay for the entire contract period. This is a common approach to securing a lower price.

Here at Spendbase our internal data shows that Daisee (Lisa) delivers strong value for contact centers, especially in accuracy, QA automation, and coaching support, with a few recurring gaps around workflow and integrations.

Overall sentiment
– Average rating across Spendbase clients is around 4.5/5.
– Adoption is particularly strong among small and mid‑size contact centers and BPOs.

What Spendbase clients like most

1) Analytics & accuracy
– High transcription accuracy, including on complex calls.
– Reliable AI scoring for compliance and quality checks.
– Strong script adherence, sentiment analysis, and risk-flagging features.

2) Time savings & productivity
– Automatic scoring of 100% of calls drastically reduces manual QA sampling.
– Being able to search transcripts, jump to keywords, and find silent gaps saves a lot of listening time.
– Leaders use dashboards to quickly target coaching conversations instead of hunting for examples.

3) Ease of setup & usability
– Out‑of‑the‑box deployment with consumption-based pricing works well for SMEs.
– Intuitive, user‑friendly interface; easy to plug into existing recording infrastructure.

4) Coaching & CX improvement
– Agent dashboards and visual graphs are heavily used in coaching sessions.
– Near real‑time post‑call insights help identify calls needing remediation and recognize good performance.

Where Spendbase clients see room for improvement

1) Functionality and workflow
– Post‑call only: no true real‑time monitoring yet.
– Difficulty linking multi-part or multi-day calls in some environments.
– UI friction: filters on both sides, losing position in call lists after listening, filters not auto-closing.

2) Data & visibility
– Some want richer dashboards and more flexible reporting views.
– Desire to override or adjust AI scores after human re-evaluation.
– Occasional issues with timestamps and call-joining in certain telephony setups.

3) Integrations & coverage
– More integrations with CRM, ticketing, and WFM tools are requested.
– English-only support and occasional struggles with heavy accents.

From a Spendbase cost-optimization angle, our internal data shows that Daisee is most cost-effective when:
– You want to move from manual sampling to automated QA on nearly all calls.
– Coaching quality and compliance are priority metrics.
– You can live with post‑call analytics and primarily English-speaking traffic.

In short, Daisee is rated as a high-accuracy, high-ROI QA and analytics layer, with the best payback in teams that actively use its dashboards and transcripts to drive coaching and process improvements.