Pitch Week . . . it's like Shark Week (but better)

So this past week has been a crazy week for the Twitter pitching community. In case you missed it, there were three pitching events going on: #NLAPitch, #PitchCB, and #SFFpit. Basically, it’s a chance for authors to pitch their MS to agents and publishers in under 140 words. 1 fave = a “bite” from said agents/publishers, meaning they’re inviting you to submit your query + first X pages/chapters to them.

Of course I had to join the party! And also, being the math nerd I am, I decided to see if I can figure out some stats from my tweets/pitches afterwards. (And also because I’m really just procrastinating since I do not want to start my plot outline. Seriously. Outlines are basically the devil-y spawns of plot synops.) In total, I pitched ten times over the course of the 3 events. And, well, here are the breakdowns . . .

***Note: There are many many unaccounted variables—such as tweet variations, online interaction, time of day when I pitched—and everything below is by no means “hard data” from a controlled observation/experiment. The point of these pitch events is to have fun, make new friends, and hopefully find an agent or publisher for your darling MS. The conclusions I attempted to draw are extrapolated (am I using that word correctly?) from the stats gathered afterwards***

***Another note: the week prior to Pitch Week, I did a quick survey of 3 different pitches to see which one people preferred. The results were pretty evenly split among the 3. All pitches I ultimately tweeted are either one of the three I polled, or some variation of them***

Some basic terms:

Likes = self explanatory; I also divided them by “agent/publisher likes” and “non agent/publisher likes”

RTs = retweets, aka, a direct retweet that will not show up in the hashtag thread again

QTs = quoted retweets, aka, an indirect retweet that will show up in the hashtag thread again if the hashtag is mentioned in the tweeted comment

Hashtag thread = the tweets that pop up when you search up #PitchEventName

The Early Pitch Gets the Likes

By “early” I mean pitches that are tweeted out within 3 hours of the event start time. For some reason, it seems as if early pitches seem to get more interaction both in terms of faves, RTs, and QTs. I think it might be because the pitch feeds can get very, very gnarly later on in the day, and many people will choose to duck out after a couple hours and only check back in sporadically throughout the rest of the day.

Spread the Love

On the pitches that did exceptionally well, not only did I send them out early, I was also very active on Twitter shortly after tweeting them. By this, I mean that I browsed through the hashtag thread and commented, RTed, QTed, or any combination thereof, of the pitches that I really liked or caught my attention (aka books I would want to read based on the pitch alone). The results? I ended up with new Twitter friends, and my pitch also got some more love in the forms of RTs, QTs, and faves! Win-win-win for everyone.

Of the ten pitches I made, 4 of them I tweeted pretty early, and the remaining 6 during the latter half of the event. The results? Well, even though I have less early pitches, I ended up with more RTs, QTs, and faves from those 4 pitches than the other 6 combined. Granted, this might also be because I was much more active on Twitter in the morning than the late afternoon/evening.

Early pitching + Online interaction = The Prime Combo (for me anyway)

Without further delay, here are some graphs of Early vs Late pitches

I’ve also ranked my pitches from “most successful” to “least successful” based on the number of agent/publisher likes below. Like I mentioned before, the most successful ones were tweeted pretty early on. (Ignore the tweet timestamps--they aren't accurate for whatever reason. I probably have it set to Greenwich time or something. Also, yes, there are only 9 pitches below because I accidentally closed the tab of my 10th pitch and I really don't remember which one it was and don't want to scroll through my old tweets again to find it. Sawry.)

A sabotaged time warp. A killchip to outwit. An alt reality to escape.
MINORITY REPORT x INCEPTION . . . in space#YA #SF #SFFpit

— T A Chan (@The_Book_Lander) June 22, 2017

Scrappy time-traveler must solve murder w/ aid of (not yet) dead man's daughter
BROKEN STARS x MINORITY REPORT...in space#YA #SF #SFFPit

— T A Chan (@The_Book_Lander) June 22, 2017

A sabotaged time warp. A killchip to outwit. An alt reality to escape. MINORITY REPORT x INCEPTION . . . in space #NLAPitch #YA #SF

— T A Chan (@The_Book_Lander) June 21, 2017

Scrappy time-traveler must solve the murder, outwit his killchip & escape alt reality before the Past merges with the Present#SFFpit #YA

— T A Chan (@The_Book_Lander) June 22, 2017

A sabotaged time warp. A killchip to outwit. An alternate reality to escape.
INCEPTION x MINORITY REPORT . . . in space#YA #SF #SFFpit

— T A Chan (@The_Book_Lander) June 22, 2017

Solve the murder. Outwit the killchip. Don't fall for the Ghost girl.
BROKEN STARS x MINORITY REPORT (but in space)#NLAPitch #YA #SF

— T A Chan (@The_Book_Lander) June 21, 2017

Solve the murder (which you might've committed). Outwit the killchip (in your head). Don't fall for the Ghost girl (really). #SFFPit #YA #SF

— T A Chan (@The_Book_Lander) June 22, 2017

Scrappy time-traveler must solve murder w/ aid of (not yet) dead man's daughter
BROKEN STARS x MINORITY REPORT ... in space#ya #sf #SFFPit

— T A Chan (@The_Book_Lander) June 22, 2017

Scrappy 18 y.o. time-traveler must solve murder w/ aid of (not yet) dead man's daughter.
MINORITY REPORT x ZENITH#NLAPitch #YA #SF

— T A Chan (@The_Book_Lander) June 21, 2017

And finally, here’s a picture of my cat. She’s a sweetie. And a buttface (nickname gained due to the fact she will sit on your face in the morning until you feed her breakfast).

Have you participated in Twitter pitching before? How was your experience?

Be sure to check out my other posts on pitching and querying HERE!

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