What TextUs and the Broader Market Charge
TextUs publishes a starting price around $300 monthly, with pricing beyond that scoped to team size and usage through a sales demo rather than a fully public tier structure, per multiple text-recruiting-platform comparison pages. Zooming out to the standalone SMS recruiting category more broadly, pricing generally runs $30 to $100 per user monthly, plus per-message or credit fees layered on top of the seat price itself, a real add-on cost that a flat monthly quote alone does not capture.
The Spread From Cheapest to Most Expensive
The range across named platforms is wide. Falkon SMS sits at the low end at roughly $15 monthly, while SenseHQ sits at the high end at $99 or more per user monthly, a more than six-fold difference between the two named examples inside the same general product category. That spread makes what does text recruiting software cost a genuinely unhelpful question without naming a specific platform and tier, since the honest answer spans an order of magnitude.
One Vendor’s Pricing Claim Worth Reading Carefully
Emissary.ai does not publish a specific price at all, but its own comparison page claims Emissary costs roughly 20% less than TextRecruit. That is a vendor’s own self-interested competitive claim about a competitor, not an independent price comparison, and it should be read as marketing positioning rather than a verified fact, the same distinction worth applying to any vendor’s claim about how it stacks up against a named rival.
A Different Tool for a Different Half of the Business
Text recruiting platforms text candidates, the sourcing and delivery side of a staffing firm’s work: reaching out about an open role, confirming shift availability, checking in during an assignment. That is a genuinely different tool category and a genuinely different audience than VA Horizon’s own model, which texts hiring managers on behalf of a staffing firm’s business-development side, working new client relationships rather than candidate pipelines. That same distinction matters on the BD side too: multi-channel prospecting, calling plus email plus LinkedIn, is already how staffing firms are described as moving past a stagnant, phone-only sales practice, per Haley Marketing’s reporting on the industry’s own sales-practice trends, and texting a hiring manager directly is a further, more direct extension of that same shift, not a variation on the candidate-texting tools priced above.
Conflating the two because both involve texting misses the point entirely. One is a candidate-engagement tool for the delivery team. The other is a new-business channel for the BD team. A firm evaluating its own software stack should budget for both as genuinely separate line items solving separate problems, not assume one purchase covers both use cases.
Whether Any of This Improves Candidate Response Rates
The category’s own comparison pages make plenty of claims about response-rate improvements, but no independently verified, disclosed-methodology study establishing a specific candidate-response-rate lift for text recruiting platforms as a category was located for this piece, and this article does not invent one. What is reasonable to say without a cited statistic: text messages get opened faster than email in most people’s ordinary phone habits, a plausible mechanism for a response-rate advantage, even without a hard, audited number attached to it here.
Getting the Software Budget Right on Both Sides of the Desk
A staffing firm weighing a text recruiting platform purchase is making a delivery-side software decision, not a BD decision, and the two budgets should be evaluated separately rather than treated as one line item. Human + AI SDRs handle the client-facing side of that equation directly, texting hiring managers to book new-business meetings, so a firm’s own software spend on the candidate side does not have to double as its BD strategy too.
Sources
The external data in this article draws on the sources below. Figures described in the text as estimates or industry triangulations are directional and are not attributed to a single dataset.