Number of Seats/Users: BigProfiles 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 BigProfiles 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 BigProfiles. BigProfiles reserves discounts for new customers or those not currently under promotional pricing.

Volume or Usage Commitment: BigProfiles 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 BigProfiles. Such companies are often in a position to negotiate for better pricing.

Early Renewal or Prepayment: BigProfiles 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 BigProfiles is generally perceived as a high‑value, easy‑to‑use AI scoring platform, with a few clear areas where clients look for better pricing or packaging.

Key positive themes our Spendbase clients highlight:

• Ease of use and speed
• Simple, intuitive interface
• Fast to deploy and quick to see first results

• Minimal manual work once CRM integration is in place

• Business impact

• Better prioritization of outbound lists and web leads
• Improved cost of acquisition and higher exploitation rates in call centers

• Versatile use cases: cross‑sell, up‑sell, churn reduction, NPL recovery, contactability, workforce management

• Quality of scoring and segmentation

• Scoring considered accurate and “confirming” or improving existing models
• Strong capabilities in segmenting by zones, sub‑zones, and custom criteria

• Ability to use the same engine across many campaigns

• Support and collaboration

• Very responsive, hands‑on data science team
• Custom solutions and continuous tuning based on feedback
• High satisfaction with the human side: availability, professionalism, and guidance

At the same time, our internal feedback also surfaces consistent friction points that are relevant for cost negotiations and contract structure:

• ROI sensitivity
• Some clients struggle to justify the added cost when BigProfiles is used on datasets already scored by partners.

• In a few cases, uplift in sales is positive but not “significant enough” yet to fully validate the spend.

• Product and workflow gaps

• Data updates and model feeds can be time‑consuming without automation.
• Cloud pilots often require manual file exchange; automation is smoother in on‑prem setups.

• Requests for:

  • More transparency on how variables are aggregated and which features drive results
  • More flexible file customization
  • Extra tools to simplify manual operations when there is no full system integration

• Adoption limits

• Some organizations haven’t exploited the platform fully due to internal constraints, not product limits—this still affects perceived value for money.

From a Spendbase perspective, this pattern suggests BigProfiles delivers strong functional value and support, but discount leverage typically appears around:
– deals for pre‑scored files,
– automation/integration gaps,
– and early‑stage pilots where uplift is still being proven.