Socialpoint x Audiencly: Dragon City and Monster Legends creator campaign

Influencer Marketing

Audiencly reports activating 362 creators for Socialpoint's Dragon City and Monster Legends, self-reporting 1.1B+ views, 23M+ likes and 1.24M+ engagements.

23M+likes
1.1B+views
1.24M+engagements

About the campaign

Socialpoint's long-running free-to-play titles Dragon City and Monster Legends needed to hold market presence and reach new players as digital habits shifted, since established live games risk fading from view when attention moves to newer titles and platforms. Audiencly's read was that for broad free-to-play games creator fit and engagement rate matter more than raw follower counts, with audiences spanning dedicated hardcore gamers to casual weekend players.

Audiencly ran a large-scale creator programme, matching influencers to the brand on fit and engagement rate rather than reach alone, and says it activated 362 creators producing content for the two titles. Platforms, formats, dates and named creators are not disclosed on the case page.

The stated logic was that matched creators drive more genuine interaction than mismatched high-reach placements, and the aggregate view counts point to a programme built for continuous presence rather than a one-off launch beat. The channel mix is not disclosed. Audiencly self-reports 1.1B+ views, 23M+ likes and 1.24M+ engagements across both games; no install, retention or revenue data is published, the numbers aggregate two titles so per-title performance cannot be assessed, and nothing is independently verified.

Case in 60 seconds

Socialpoint's long-running free-to-play titles Dragon City and Monster Legends needed to hold market presence and reach new players as digital habits shifted.

For broad free-to-play games, creator fit and engagement rate matter more than raw follower counts, and gaming audiences span hardcore players to casual weekend players.

Run a large-scale creator programme, matching influencers to the brand on fit and engagement rate rather than reach alone.

Audiencly says it activated 362 creators producing content for the two titles; platforms, formats and dates are not disclosed on the case page.

The agency self-reports 1.1B+ views, 23M+ likes and 1.24M+ engagements across the work. No independent verification or business outcomes are available.

Strategy Breakdown

The primary strategy-learning section — interpretation, not a press-release summary.

Mobile gaming audiences from dedicated hardcore gamers to casual weekend players, matching the broad player base of free-to-play titles.
Based on the agency's framing, established live games risk fading from view in a shifting digital scene where attention moves to newer titles and platforms.
Free-to-play mobile games depend on a continual inflow of new players, so visibility has to be sustained rather than won once.
Place Dragon City and Monster Legends at the heart of the gaming community through creators the audience already watches.
The agency's stated selection filter was brand fit and engagement rate, on the basis that matched creators drive more genuine interaction than mismatched high-reach placements.

Creative & Execution System

Assets & channels

  • Creator-made content; formats and platforms not disclosed on the case page

Partners

  • 362 creators (not named individually)

Participation mechanic

  • Sponsored creator content
  • Creator selection by brand fit and engagement rate

Creator role

  • Gaming creators producing content featuring Dragon City and Monster Legends

Results & Evidence

MetricValueResult typeConfidence
Views1.1B+reachAgency reported
Likes23M+engagementAgency reported
Engagements1.24M+engagementAgency reported

Why Audiencly's strategy worked

  1. 1

    Long-running live games can use a large creator roster to sustain visibility rather than relying on a single burst; the agency claims 362 creators here.

  2. 2

    Selecting creators on brand fit and engagement rate is a sensible filter when the goal is broadening an audience across hardcore and casual players.

  3. 3

    Aggregate view counts at this scale suggest a programme built for continuous presence, not a one-off launch beat.

  4. 4

    Self-published metrics without dates, platform splits or downstream outcomes limit what buyers can conclude; ask for install and retention data behind the view counts.