LinkedIn ad impressions refer to the number of times a LinkedIn ad is displayed on a user’s screen. This metric indicates how many opportunities your ad had to be seen by LinkedIn users. However, it does not measure how many people actually viewed or engaged with the ad. Impressions are a key metric used to measure ad reach and visibility.
How do LinkedIn ad impressions work?
LinkedIn impressions are counted each time your ad loads on a LinkedIn page. This includes:
- When a user’s newsfeed refreshes and your ad appears
- When a user navigates to a new page and your ad loads
- When a user scrolls through their feed and your ad comes into view
An impression is counted even if the user does not click or interact with your ad. As long as your ad loads on their screen, it counts as an impression. The number of impressions your ad receives will depend on your targeting, bid, budget, and other factors.
Why do LinkedIn ad impressions matter?
LinkedIn ad impressions are important for several reasons:
- Measuring reach: Impressions show how widely your ad reached LinkedIn users. More impressions mean greater visibility for your brand.
- Frequency: Along with reach, impressions indicate the frequency your ad was seen. Higher impressions often correlate to increased brand awareness.
- Campaign optimization: Analyzing impression volume and frequency helps optimize future campaigns for improved results.
- Benchmarking: Impressions allow you to benchmark different campaigns and creatives against each other.
While other metrics like clicks and conversions are important, impressions provide the foundation to evaluate overall campaign effectiveness. High impression volume indicates your targeting and placements are dialed in.
How many LinkedIn ad impressions are good?
There is no universal “good” number of LinkedIn ad impressions. The ideal impression volume depends on factors like your goals, targeting, and budget. However, here are some benchmarks for LinkedIn ad impressions:
- Awareness campaign: 100,000+ impressions
- Traffic campaign: 50,000-100,000 impressions
- Lead gen campaign: 10,000-50,000 impressions
- Brand new campaign: 5,000-10,000 impressions
Aim for enough impressions to meet your campaign objectives. For example, heavily targeted leads campaigns may only need 10,000-20,000 impressions. Broad awareness campaigns should tally much higher impressions to reach their audience.
How to increase LinkedIn ad impressions
Here are some tips to drive more LinkedIn ad impressions:
- Broaden your targeting to reach more users
- Increase your daily ad budget to serve more impressions
- Use all available LinkedIn ad placements (feed, right rail, etc.)
- Test multiple ad variations to find high-performing creatives
- Segment your audience for relevant messaging
- Ensure ad relevance with effective targeting
- Optimize ad copy, visuals, and calls-to-action
By optimizing these elements, you can increase the volume of LinkedIn users your ads reach on a daily basis. Just avoid focusing solely on driving impressions at the expense of relevant targeting.
How much do LinkedIn ad impressions cost?
The cost per LinkedIn ad impression varies significantly based on factors like:
- Targeting parameters
- Competition for keywords/audiences
- Ad placement (feed vs. sidebar)
- Bidding strategy
On average, LinkedIn ad impression costs range from $0.50-$3.00. Narrowly targeted campaigns tend to be more expensive per impression compared to broad-based awareness campaigns. Here is a breakdown of average LinkedIn ad impression costs:
Targeting | Avg. CPM |
---|---|
Broad awareness | $0.75 – $1.50 |
Industry/job role targeting | $1.00 – $2.00 |
Specific companies | $1.50 – $3.00 |
Use these benchmarks to set realistic CPM expectations. Closely monitor impression costs to allocate budget efficiently.
Tips to decrease LinkedIn CPM
If your current LinkedIn CPM is too high, here are some ways to lower it:
- Broaden your targeting to expand reach
- Test lower cost ad placements like the feed
- Adjust your bid strategy from “Auto” to “Manual”
- Set a lower max CPM bid to reduce competition
- Create ad variations to find high-performing creatives
- Only target highly relevant audiences
- Run ads consistently to take advantage of optimization
- Take advantage of LinkedIn’s CPM discounting based on spend
With some optimization, you can likely decrease your LinkedIn CPM to under $2 for broader targeting. Monitor impression volume as you lower CPM to ensure you’re still reaching your audience.
How to calculate LinkedIn ad CTR from impressions
You can calculate your LinkedIn ad CTR (click-through rate) by dividing clicks by total impressions:
LinkedIn Ad CTR = (Clicks / Impressions) x 100
For example, if your campaign received:
- 5,000 impressions
- 250 clicks
Your LinkedIn ad CTR would be:
(250 clicks / 5,000 impressions) x 100 = 5% CTR
Benchmark CTR varies by objective and placement, but tends to fall in the 0.5-2% range for the LinkedIn feed. Calculate CTR to gauge ad relevance and optimize creatives, messaging, and targeting.
Should you optimize for LinkedIn impessions or CTR?
In most cases, you should not solely optimize LinkedIn campaigns for impressions or CTR. The best practice is to focus on driving relevant impressions that convert into your KPIs like leads or signups. Some tips:
- Set a target CTR based on benchmarks for your objective
- Aim to drive enough impressions to meet campaign goals
- Review impression share data in LinkedIn ads
- Increase bids if needed to get a high percentage impressions share
- Use LinkedIn’s tracking and optimization capabilities
- Measure downstream conversion rates in addition to CTR
With a balanced approach, you can drive quality impressions that convert.Neither an extremely high or low CTR is ideal if it comes at the expense of meeting your campaign KPIs.
How LinkedIn ad impressions are calculated
LinkedIn provides in-depth metrics on ad impressions within Campaign Manager. Here is how LinkedIn calculates and attributes impressions:
- Single impression per ad view: Only one impression is counted per time the ad appears on screen.
- Cross-device impressions: If a user sees the ad on multiple devices, each impression counts separately.
- Attribution window: Impressions are counted when the ad first loads on screen. Any resulting clicks or conversions are attributed to that impression if they occur shortly after.
- Bulk impression counts: LinkedIn tallies up all qualifying impressions across a campaign for reporting.
- Audience overlap: If you target overlapping audience segments, LinkedIn de-duplicates reach to avoid inflating impressions.
This methodology allows you to accurately analyze your LinkedIn ad results and attribution. Make sure to dig into the detailed impression metrics available in Campaign Manager.
Impression metrics to analyze
When evaluating LinkedIn ad results, look beyond just the total impressions number. Here are some key LinkedIn impression metrics to analyze:
- Impression share: % of potential impressions you captured vs. competitors.
- Impression frequency: Average times each user saw your ad.
- Daily impressions: Track impression volume day-by-day.
- Impressions by ad: See impression breakdown for each ad creative.
- Impressions by audience: Assess performance for each target segment.
- Impressions by placement: Compare feed vs. sidebar vs. text ad volume.
Segmenting your LinkedIn impression data provides optimization insights. You want to drive relevant, quality impressions from the right audiences across placements.
Should you use LinkedIn impressions to measure awareness?
Due to how LinkedIn counts ad impressions, this metric does not necessarily correlate directly to awareness. Some best practices include:
- Combine impressions with survey data for true awareness measurement.
- Calculate an average frequency cap to estimate unique reach.
- Analyze impression share and saturation among your target audience.
- Factor in viewability – not all impressions truly have an opportunity to be seen.
- Supplement with brand lift studies or surveys to tie impressions to recall.
Impressions alone are not a perfect proxy for awareness. But high impression volume is generally required to drive increased brand visibility and familiarity. Use impressions directionally along with other metrics to gauge awareness lift.
Should you use LinkedIn impression share as a benchmark?
LinkedIn’s impression share metric can provide a helpful benchmark for ad positioning. Impression share shows what % of available impressions your campaign captured vs. competitors. Some tips on using impression share:
- Aim for a high (90%+) impression share within your target audiences.
- Low impression share indicates your targeting is too broad or bid is too low.
- Monitor impression share trends day-by-day.
- Break down impression share by audience, placement, device.
- Increase bids or budget if needed to improve impression share.
Think of impression share as an indicator of how competitive your positioning is to reach your audiences. Benchmark against other campaigns and aim to increase over time.
Should you report on LinkedIn impression frequency?
Monitoring LinkedIn ad impression frequency is recommended to understand how often your target audiences are exposed to your messaging. Some key points:
- Higher impression frequency improves brand awareness lift potential.
- Avoid excessive frequency caps that reduce relevance.
- Look at impression frequency by device and audience segment.
- Aim for ideal frequency based on campaign goals.
- Adjust targeting, placement and creatives to manage frequency caps.
Analyze impression frequency trends in Campaign Manager. The ideal frequency cap varies, but 2-4 times per month is a typical average target range.
Conclusion
LinkedIn ad impressions indicate the reach and visibility of your campaigns. While not a perfect awareness metric, higher (relevant) impressions correlate to increased brand exposure. Monitor beyond just total impressions to analyze metrics like impression share, frequency, and placement breakdowns.
Aim to drive enough impressions among your target audience to achieve brand lift and campaign goals. But avoid focusing solely on chasing impressions without regard to quality. The right impression benchmark varies by factors like objectives and audience size. Optimize over time based on performance data.