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Microsoft Dynamics 36511 min read

The Dynamics 365 Partner Review Landscape: What Current Review Records Show

By George Brown

A methodology-first look at 1,210 Google and 495 Glassdoor partner records in one unique public Dynamics cohort.

TL;DR

  • Ratings can be useful when you are shortlisting a Dynamics 365 partner. They are not a substitute for checking fit, delivery experience, references, scope, or commercials. This analysis rebuilds one stable cohort of 1,507 unique public, non-hidden Dynamics VAR and mixed-model partners from the current directory.
  • Snapshot: queried July 23, 2026 at 9:06 PM UTC; newest included source or theme timestamp June 23, 2026 at 11:39 AM UTC; method 2026-07-23.v2.
  • Among 949 partners with a usable Google rating, the unweighted partner average is 4.55 out of 5. Review volume is uneven: 426 partners have 1–5 Google reviews, 313 have 6–20, and 210 have more than 20.

Ratings can be useful when you are shortlisting a Dynamics 365 partner. They are not a substitute for checking fit, delivery experience, references, scope, or commercials. This analysis rebuilds one stable cohort of 1,507 unique public, non-hidden Dynamics VAR and mixed-model partners from the current directory.

Snapshot: queried ; newest included source or theme timestamp June 23, 2026 at 11:39 AM UTC; method 2026-07-23.v2.

What the two review sources measure

The cohort contains Google source records for 1,210 partners containing 26,875 Google reviews and Glassdoor source records for 495 partners containing 104,434 Glassdoor reviews. 421 partners have a source record on both platforms. Google usually reflects customers, prospects, visitors and local interactions; Glassdoor is employee- and candidate-authored. Neither is a direct implementation-quality measure.

Google ratings are concentrated at the high end

Among 949 partners with a usable Google rating, the unweighted partner average is 4.55 out of 5. Review volume is uneven: 426 partners have 1–5 Google reviews, 313 have 6–20, and 210 have more than 20.

Google rating distribution by partner Five rating bands count 949 distinct eligible partners with a usable Google rating. 1.0–1.982.0–2.9133.0–3.9764.0–4.42094.5–5.0643
Partners per Google rating band; each partner contributes once.
Google rating bandDistinct partners
1.0–1.98
2.0–2.913
3.0–3.976
4.0–4.4209
4.5–5.0643

Glassdoor has a different shape

Among 495 partners with a usable Glassdoor rating, the unweighted partner average is 3.74 out of 5. Different audiences and review processes mean the distribution should not be read as a direct scorecard against Google.

Glassdoor rating distribution by partner Five rating bands count 495 distinct eligible partners with a usable Glassdoor rating. 1.0–1.982.0–2.9513.0–3.92344.0–4.41174.5–5.085
Partners per Glassdoor rating band; each partner contributes once.
Glassdoor rating bandDistinct partners
1.0–1.98
2.0–2.951
3.0–3.9234
4.0–4.4117
4.5–5.085

Where the two ratings land for the same partner

The paired view contains 340 partners with usable records on both sources. Their unweighted averages are 4.47 on Google and 3.75 on Glassdoor. Each point below is a real paired partner record; deterministic jitter makes identical rating pairs visible without changing either value.

Google rating bandGlassdoor 1.0–1.9Glassdoor 2.0–2.9Glassdoor 3.0–3.9Glassdoor 4.0–4.4Glassdoor 4.5–5.0Row total
1.0–1.9032005
2.0–2.9001102
3.0–3.914199134
4.0–4.4065720891
4.5–5.0219875149208
Column total3321668158340

What the tagged review themes surface

The directory holds validated AI-generated client-review theme tags for 576 eligible partners, with 9,222 stored tag occurrences. Theme rows are deduplicated by listing ID before aggregation. These are labels applied to review text, not a survey or independent performance measure.

Most frequent client-review theme labels Blue bars are the five most frequent positive labels and amber bars are the five most frequent negative labels. Counts are stored tag occurrences after one theme row per partner. Professionalism643Client Satisfaction359Service Quality261Customer Service224Technical Expertise199Communication Issues50Customer Service32Customer Support30Communication26Responsiveness21
Top five positive labels followed by top five negative labels; labels can appear in both groups.
Positive labelStored tag occurrencesNegative labelStored tag occurrences
Professionalism643Communication Issues50
Client Satisfaction359Customer Service32
Service Quality261Customer Support30
Customer Service224Communication26
Technical Expertise199Responsiveness21
Customer Support168Service Quality19
Responsiveness129Billing Issues18
Expertise128Project Management12
Support Quality115Professionalism11
Reliability84Reliability11

A practical way to use review evidence

  1. Use the partner directory to identify firms with the product, industry and geography you need.
  2. Read recent reviews, not only the aggregate score; note whether the reviewer context is customer- or employee-facing.
  3. Ask shortlisted partners for references similar to your implementation scope and complexity.
  4. Use the comparison tool to put specialization, service and directory information side by side.
  5. Discuss recurring themes directly and test the answer against references and the proposed delivery plan.

Methodology and limits

The denominator is rebuilt from listings_v2 using status = 'active' AND website_hidden_at IS NULL AND dynamics_partner_type IN ('var', 'mixed'). Eligible IDs use stable ORDER BY id pagination, are deduplicated before related queries and must match an independent server-side exact count of 1,507 partners with zero repeated IDs. Review rows are canonicalized once per listing and platform; legacy google_maps is grouped into Google and a current google row wins when both exist. Usable values require a stored 1.0–5.0 rating and an integer review count of at least one. Theme rows are reduced to one latest row per listing ID before labels are aggregated. Rating averages are unweighted by review count.

Coverage is not random. Missing profiles, platform audiences, moderation, review age and AI-assisted theme classification all limit inference. This article does not rank partners or infer customer outcomes from ratings.

Share this analysis

LinkedIn: We rebuilt a unique cohort of 1,507 public Dynamics VAR and mixed-model partners and paired current Google and Glassdoor records without double-counting. The result is a due-diligence aid, not a partner ranking. →

X: 340 D365 partners have usable Google + Glassdoor rating pairs in the current public cohort. See the accessible scatter, distributions and methodology →

George Brown
George Brown

Co-Founder & CEO

George Brown has over 40 years of experience in the Microsoft Dynamics ecosystem, including leadership roles at Partner Economics, Jet Global, and Aston Group NA.

Microsoft Dynamics Expert40+ Years ERP Experience500+ ERP Implementations Overseen

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