Social Timing Insights

* ArgyleSocial argylesocial.com Social Timing Insights Understanding the science behind timing and its impact on social media marketing performance. Brands want to time posts to achieve maximum engagement. But when are their customers most receptive? We inspected a segment of our customer data - 250K posts and 5M clicks – to see if we could identify aggregate trends. When are marketers posting? B2B B2C midnight ба noon бр Sun Mon Tue Wed Thu Fri Sat midnight Daily post volume Daily post volume Marketers, by and large, post when they are at work instead of when their audience is listening. Post timing should be used strategically to maximize engagement. B2B B2C When is engagement the highest? f Facebook Weekday +2% Weekday -16% Weekend -2% Weekend +16% B2B Facebook: too close to cal. B2C Facebook: Marketers get better +32% engagement on the weekends. Twitter Weekday +7% Weekday -4% Weekend -7% Weekend +4% B2B Twitter: Marketers get better engagement on weekdays. B2C Twitter: too close to call. +14% Weekdays B2B Weekends B2C f Facebook times Morning (4a-9a) +3% Morning -40% Daytime (9a-7p) C Night (7p-40 +9% Daytime 0% -15% Night +6% B2B Facebook: Post engagement is consistently higher during the day. B2C Facebook: Engagement is notably higher in the evenings on weekends. Monday +5% Tuesday +2% Wednesday -13% Thursday 0% Saturday -15% Friday +8% Sunday +15% B2C Facebook: Sunday shows notably that's my higher engagement than Saturday. B2B Facebook: too close to cal. fun-day. Twitter times Morning (4a-9a) -5% Morning -9% Daytime (9a-7p) +4% Daytime +8% C Night ( -20% Night -21% B2B Twitter: Post engagement is consistently higher during the day. B2C Twitter: B2C marketers see the bes engagement on Twitter during the dayt Monday +3% Tuesday +2% Wednesday -3% Thursday -1% Saturday -6% Friday -1% Sunday +6% B2B Twitter: too close to call. B2C Twitter: too close to call. The Good & Bad of Social Timing Bad: Good: Averages & Trends Scientific Method @snoopdogg should tweet at 13:15 Hypothesis 100 "I think that I will get more lift by scheduling my morning 80 posts at 8am instead of 10am." Experiment drop it like it's hot! Build a plan and tracking methodology to get to the right answer. Analyze The highest point on a trend line isn't a statistically valid or "Hmmm! The data tells me that my hypothesis is correct! .or not" actionable answer! ArgyleSocial Data-Driven Social Media Marketing argylesocial.com y argylesocial