So I wrote a book—now what?
Well, I have two options: Traditional Publishing or Self-Publishing. Both are respectable avenues with their own sets of pros and cons—but that’s a topic for another day.
In my case, when I first shared The Valkyries with a friend and found the courage to step on the path toward publication, I chose Traditional Publishing.
The first step? Write a book. Check.
The next step? Sharpen it. Check.
After that? Sharpen it again. And Again. And again. Check. Check. Check.
Then, after tying up as many loose ends as I could, after sharing with friends, family, and beta readers, I would need an agent to help secure a deal with a publisher.
But I couldn’t just blast my manuscript blindly to agents hoping they would hop on board. Every agent has their own wishlist, their own areas of expertise, their own connections within a genre.
So I had to do some research—and this is where my skills in data collection and analysis could finally shine again!
With really only two websites that I’ll share below, I compiled a list of 213 agents open for queries who had listed themselves open to manuscripts under the Fantasy genre, and filtered it down to 143 potential matches.
Let’s see how I did it (with all agent information redacted, of course), in four main steps:
QueryTracker
I started with QueryTracker (QT), where I managed to find agents interested in Fantasy manuscripts.
QT offers a free version and a premium version, and to be fully transparent, I don’t think I’ve fully leveraged the benefits offered by the premium version (yet), but at only $25 per year (yes, per year), I’m not too concerned about it.
To get my list of agents, I filtered for agents interested in any type of fantasy, because even though The Valkyries falls under the Fantasy, High/Epic subgenre, many agents don’t silo themselves to that level.
Then, I checked the boxes for Hide Closed Agents and Hide Do-Not-Queries so I would only see agents interested in Fantasy who were also open for queries.
With those two simple steps, I had my list of 213 agents and the links to their agencies—a great help in finding their most recent wishlists.
But before I left QT, I made sure to collect as much data on each agent as I could. This included their response timing, breakdowns between positive and negative replies, how often they request manuscripts, and so on across 20 different sets of data.
I collected the data, yes, but I didn’t disqualify any agents from what I found—I merely used a handful of metrics to help as a kind of “tie-breaker” should I be undecided between which seemingly equal agents I should query first.
These metrics included:
- Query Reply Rate
- % Positive Query Replies
- Request Rate
- % Positive Submission Replies
- Average Positive Reply Time
And here’s how it looked on my tracking sheet, where I assigned a weight to each category to calculate the agent’s “score,” an arbitrary number used only as a way to sort my list.
Manuscript Wishlist
Satisfied with what I found, I moved on to the next site: Manuscript Wishlist (MSWL).
But before I continue, I have to admit I could have gone straight to each agent’s agency website instead to find their wishlists, because from what I was able to find, only 92 of the 213 agents on my list (43%) maintained a profile page on MSWL.
And even then, the content on MSWL was either nearly identical to what I found on their agency website, or their website linked straight to MSWL anyway.
Could I have saved a few minutes? Sure, but it was still worth my time exploring another source of potential information.
Anyway, back to my data scavenging in MSWL.
Just like QT, MSWL has a search feature, so I first started searching for agents by name one by one to read their profiles.
After quickly realizing that (a) too many agents didn’t have profiles and (b) the URLs for the agents who did have a profile all followed the same structure, I wrote a formula in my spreadsheet to create the URLs manually, expediting my time searching for each agent’s MSWL page.
If you’re curious, the URL structure is:
https://www.manuscriptwishlist.com/mswl-post/firstname-lastname/
With some moderate spreadsheet skills, you can write a formula to create that link based on the agent names collected from QT—assuming you’re tracking your potential agents in a spreadsheet.
There’s not much more I can share from MSWL without showing an agent’s page, so in the interest of not over-sharing, you can go straight to the search page I used and take a look yourself.
Please note, the agents you may see already populated on that page are not necessarily agents on my list—it looks like MSWL starts populating the search results starting with agents whose first name starts with an “A.”
Agency Sites
Like I said, over half the agents on my list didn’t have profiles on MSWL, so I backtracked to QT. From there, I found each agent’s QT profile page and their agency’s website. This led me to the agent’s page—and their wishlist.
I reviewed every one. I checked to see strongly they were looking for Fantasy on their wishlist.
But I also checked for dealbreakers.
I needed to find anything that would make me and/or The Valkyries a bad fit for them—and anything that would make them a bad fit for me. It’s nothing personal. Not every agent is a good match for every writer, and vice versa. Better to discover that now instead of later, saving both of us time.
Now, assuming I found no dealbreakers, I classified them as one of five tiers based on their wishlists:
- Dream Agent: They’re actively acquiring science fiction and fantasy (SFF) with a focus on high/epic fantasies (i.e. The Valkyries).
- Strong Contender: They’re ctively acquiring SFF, but may be focused on other subgenres.
- Low Priority: They have Fantasy on their wishlist, but they’re either less focused on fantasy, or they’re outside of the United States. International agents could work, but as a debut author who wants to publish domestically and who is not familiar with what the process would look like with an international agent, I preferred to keep it simple.
- Likely Pass: Fantasy is on their wishlist, but they may be focusing on other genres at the moment, or there are a couple potential dealbreakers moving them lower on my priority list.
- Pass: They’re no longer representing Fantasy, closed to queries, or have other specific requirements I do not meet (i.e. marginalized writers).
This review spanned several days and carved my list of 213 agents down to 143 potential candidates—Dream Agents, Stronger Contenders, and Low Priorities.
And with every review, I tracked their profile and wishlist, my notes and comments, their wishlist rating, and links to their QT, MSWL, and agency pages.
This way, when I got to the point that I would be ready to query that agent, I would have easy access to all their information I had previously reviewed myself.
With this list, I had all the information I needed to know about who I should and shouldn’t query.
But I had 143 names to pick from.
That’s a bit much, don’t you think?
So, where do I start?
Publishers Marketplace
I had one more dataset to consider—this time, from Publishers Marketplace (PM), which requires a $25 per month subscription. For the level of information I was able to get—and for the vast amount of other information I’ve yet to leverage—I’d say it was worth it!
Same as QT and MSWL, I used PM’s Dealmakers search tool to find each of my agent’s page and view their list of “deals,” the books they’ve represented.
Each agent’s page provides all the information I could need—total deals, dealmaker rankings, breakdown of deals per category—but most of all, the dataset I ended up relying on most: deals in the last 12 months.
Just like before, I copied and pasted the list into my tracking sheet, and reviewed each deal to see how it aligned with my genre.
Then, I assigned a separate ranking to each agent:
- Recent Deals: They completed deals in epic/high fantasy in the last 12 months.
- No Relevant Deals: They did not complete deals in epic/high fantasy in the last 12 months.
- No Deals: They did not complete any deals in the last 12 months.
Even if an agent fell in the second or third category, I kept them on my list of 143.
Why? Because in my mind, sure, they were not as active in the Fantasy genre, but that could mean no Fantasy queries had crossed their desk in the past 12 months that sparked their interest. So, instead of knocking them off the list, I simply prioritized them lower.
Maybe The Valkyries could be the deal that brings them back to the Fantasy genre!
Here’s what my tracking sheet looked like now for each agent, where “PB Rating” shows how I rated the agents on their deal flow.
From QT, I had their name, agency, location, and agency website (which led me to the main wishlists I used).
From MSWL, I had a glimpse at their wishlists (for those who had a page).
From their agency pages, I filled the gaps in any missing wishlists to help me finish rating each agent in my tier system.
From PM, I had all the deals each of my 143 potential agents completed in the last 12 months.
And here’s how the final numbers look:
I already know what you’re saying: that’s quite the eye-chart.
But honestly, I’m not using this chart specifically: I made it just to show how the numbers panned out.
What I do use is the sheet where I tracked each agent’s individual ratings in the various categories, using those to formulate a “Sort ID.” I use the Sort ID to sort the list of agents from best match to lowest based on the criteria below and in this order:
- Are they a potential match (wishlist tiers 1, 2, or 3)?
- Are they in the United States?
- What wishlist tier did they fall in (1, 2, 3, 4, or 5)?
- What deal history tier did they fall in (1, 2, or 3)?
- What is their agent rank based on their metrics in QT?
After generating a Sort ID for each agent, I sorted my list of 213 agents by that ID to see my agents listed from best match to worst match.
You may think my first wave of queries went to the agents at the top of the list, but because I’m new to this game, I decided to send them to the last five agents in the United States in tier 1 for wishlists and deal history. That way, if I royally screwed something up in my submission package, it lessens the blow.
And there you have it: how I gathered my list of 143 potential agents and how I prioritized them to send queries for The Valkyries.
In a future post, I will show how I deep-dived the list of 584 deals to see where Fantasy ended up on the deal count rankings.
Good news: it’s high on the list!
Looking Back
Why did I go through all this trouble?
Because from everything I’ve read, the Query Trenches can be a nightmare, so I scouted the battlefield first, finding the best points to strike.
Or in this case, the right agents to query, and how.
Will this actually save me time in finding the right agent for The Valkyries? Only time will tell. Join the Shieldwall and you’ll be among the first to find out when I do.
But even if I end up waiting in purgatory as long as someone who skipped their research, at least I march forward with clarity—and a plan of attack.
JOIN THE SHIELDWALL
Join our newsletter for early access to updates, behind-the-scenes looks, and upcoming exclusive content!
