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

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

Early Renewal or Prepayment: AdRoll 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 AdRoll is seen as a solid, mid-market retargeting and e‑commerce advertising tool, but with a few important caveats that procurement and marketing teams should factor into renewals and negotiations.

Overall sentiment
– Most Spendbase clients rate AdRoll positively for:
– Ease of initial setup
– Strong retargeting capability (especially for smaller e‑commerce brands)
– Helpful creative support (designing ads and dynamic banners)
– At the same time, there’s a meaningful cluster calling out:
– Clunky UX and confusing attribution
– Limited targeting depth
– Inconsistent support quality
– Questionable cost-effectiveness at scale

What Spendbase clients like
Our internal data shows that clients most often praise:
– Simplicity:
– Quick to get started, tag installed, and basic campaigns live
– Dashboards that are “simple” and “intuitive” for non-experts
– Retargeting performance:
– Good ROAS for many e‑commerce setups
– Strong Facebook retargeting in particular
– Smart segmentation and reach across channels (display, social, email)
– Extra services:
– Free or supported ad-creative production when teams are stretched
– Automation that lets campaigns “mostly run themselves”

Where things break down
Our internal data also shows recurring friction in a few areas:
– Targeting & features:
– “Too basic” or “starter level” for medium/large stores
– Limited granular control, especially for premium brands and advanced marketers
– Reporting & attribution:
– Simple but not very deep; lack of granular analytics
– Mismatch with Google Analytics and opaque attribution logic
– “Black box” optimization with little visibility into what the algorithm uses
– UX & platform reliability:
– Confusing separation between bid strategy and optimization settings
– Occasional bugs, slow ad browsers, and friction with conversion setup
– Support & account management:
– Experience varies greatly by rep; some rave about support, others cite slow, fragmented help
– One severe case of months-long technical issues and non-functioning Meta integration

Cost & fit
From a Spendbase discount perspective, our internal data shows:
– Great value for:
– Small to mid-size e‑commerce teams needing plug‑and‑play retargeting
– Companies that benefit from bundled creative services
– Potential overspend risk for:
– Teams that could run retargeting effectively in-house (Meta/Google directly)
– Larger brands needing granular control, reliable integrations, and deep analytics

Net takeaway: AdRoll can be a cost-effective part of the stack for simpler, growth-focused commerce brands, but Spendbase clients should push hard on pricing, SLAs for support, and clarity around attribution and optimization before committing.