Archive for September, 2009

A Google Settlement I Could Support

Monday, September 28th, 2009

So, the original Google Settlement is dead, dead (spell that D-O-J: dead). As frequent readers of this blog may remember, I wasn’t too enthused about it, and I won’t be grieving.

I do, however, hope that some version does come to fruition. I think it has the potential to make enormous sums for most small and micro-presses, and to keep authors’ work alive for a far longer time.

It might even help reverse the steady decline in book reading that has afflicted this country.

What would I like to see in that agreement?

1. Compensation for the infringements to date going not to rightsholders, but to the formation of the rights registry. The proposed compensation in the old agreement was so small per title as to be utterly useless, but in the aggregate, it could move many mountains. That registry could benefit all of us in much larger ways, and forcing Google to pay for it will ensure that no other corporate behemoth gets the idea that they can infringe with impunity.

Part of the cost of establishing this registry would include widespread advertising in the US and elsewhere covering how the works can be claimed, or registered if not yet scanned, and where. It should also be possible to try to port the LOC rightsholder database over to the new registry.

2. All non-search uses on an opt-in basis ONLY during the life of copyright. This is critical, because anything less eviscerates all of copyright. It’s a precedent we cannot allow.

3. Search results displaying a reasonable amount (half a page? A whole page?) on an opt-out basis for all book length works. This is an exact parallel to web search (which has already been tested and found to be fair use), and is critical to growing our knowledge base. To do this, Google will get the right to scan anything not excluded by the rights holder. Google can monetize this with ad display, as is currently done for web sites.

4. Opt-in only licensing to libraries. A reasonable split would pro rate the licensing fees by the length of the file covering each work, payable to all rights holders as long as the work is in copyright.

5. Opt-in only licensing of the right to sell ebook, POD and other versions of the works in the database. I liked the 65/35 split between Google and the rights-holders. It seems reasonable.

So where do those enormous sums come in?

6. Every time someone clicks on a book search link, the page should include a free ad for the book. And if the book is available through their site or a major on-line source, it should include links to those sellers. Affiliate links, perhaps, so that Google gets a commission, but links nonetheless. I suspect that this will greatly increase book sales, especially for small presses and self-published authors.

I’m sure I missed some important points. What would you like to add?

Marion’s Rules of Publishing

Friday, September 25th, 2009

This isn’t complete, and I’ll try to keep adding to them, but here are a few of my favorite rules:

1. You may get what you pay for, but you rarely get much more.
Great, cheap alternatives usually have a catch.

2. Crunch your numbers.
If you’re making a decision that can have a major impact on your results, always test the alternatives, and compare the changes in your bottom line. (If you don’t know how, read the rest of my blog, take a seminar I offer at one of the publishing conferences near you or ask a question in the comments!)

3. It depends.
You’ll hear a lot of general rules pronounced (including this list). Most of them are true for at least some circumstances. But all of them have exceptions. Look at the situation in front of you, and think it through, rather than relying upon a rule.

4. There are NO shortcuts in this business.
There are, however, a large number of very attractive routes leading to heartbreak.

4A. Those dinosaurs, the “big NYC publishers,” are run by some very smart people.
If they’re not doing something that seems simple and obvious to you, the chances are pretty good that you’re missing something.

5. Success at self-publishing is harder than getting published by a mainstream house.
(IF you define success in terms of exposure, fame or profit.)

6. I repeat: crunch your numbers!

Estimating Sales, Part IV: Using Public Databases

Thursday, September 24th, 2009

It’s important to do more than one estimate of your titles’ sales. Why? Because each set of data you use will give you a different number, and all of them will be wrong in different ways. If you average them, you get a better chance of a good prediction. Of course, if you could pick the best estimate from the bunch, you’d be closer, but which one is it? I don’t know, and you probably don’t either.

The previous 3 parts of this series dealt with the use of experience, marketing plans, and Amazon data on comparable titles to predict the sales of either that comp or of your book. Part V will discuss using sales of comps to predict sales of your title, and then combining all of the various predictions into an overall prediction of sales for your title.

This part of the series covers projecting the sales of comparable titles from other sources of data, and combining all the various projections of comparables’ sales. The best sources of data besides Amazon are Bookscan, Ingram, and perhaps the data your friends inside other publishing companies are willing to share. (That last is an old industry tradition that is fading slowly as the industry expands and changes.)

So, you have a list of carefully chosen comparable titles. They’re all from companies that are distributed in similar ways, and they all have similar marketing muscle behind them. They’re all aimed at the same audience, and are intended to fill similar needs.

Now what? Well, Ingram has the iPage facility. Use it to get a good idea of what Ingram’s volume has been for each of those comparables over the past few months or a year. Bookscan also offers good data on sales.

Ingram is, of course, the primary wholesaler to the book trade. You should know roughly what fraction of this type of book’s sales will go through them. For many trade books, it will be something like 50%, but for others, it will be much more or much less.

Bookscan records approximately 70% of the sales by general bookstores. Obviously, the publisher will be selling more to the bookstore than the store has moved out of the doors, but this is still a solid number. It may not be very helpful to you, though, if you’re doing books that don’t move through bookstores and similar retailers.

If you have those numbers for a “bookstore book,” or even for one that will sell a significant share of the total through stores, you can make a pretty good estimate of the total sales for that comparable title.

To go from the fraction that went through a channel, say Ingram, to the total sold, is simple. Divide the sales by the fraction. For example, let’s say that half of your books generally go through Ingram. And that you know your comparable title sold 1,000 copies through Ingram. Divide that 1,000 by 1/2, and you get 2,000. That’s your estimate of how many copies that comparable title sold — based upon the Ingram data.

For Bookscan, it’s only slightly more complex. You divide Bookscan’s report by .7 to arrive at the estimated bookstore sales, and then divide that result by the fraction that you expect to distribute through bookstores. That result is the Bookscan-based estimate of your comparable title’s total sales.

If you have an estimate of the sales through Amazon (from Part III), you can gross that up to an estimate of total sales for that title, by again dividing by the fraction of total sales that you expect to make through Amazon. (For trade books from a mid-sized publisher, that might be .15, for example. For niche non-fiction from a micro-publisher, that number might be as high as 75 or 80%.)

To make ANY estimate better, you can combine a number of different versions that are based upon different data sources. If you average them, you should help remove any random error. Here, you’d take all three estimates of total sales for each comp (based on Ingram, Bookscan and Amazon numbers), add them together, and divide by 3. [Yes, I know you know how to average. Just being complete.]

CAVEAT: This doesn’t always work. If Murphy is out to get you, all the errors will be in the same direction, perhaps because of some underlying and confounding variable that’s not properly understood.

My response to this issue: if my judgment says that the results don’t make sense, I either dig further to find the problem, or ignore the estimates. Do NOT, NOT EVER, ignore that little voice in your head that says something’s wrong.

Any questions out there? Come on, ‘fess up. I’m pretty sure my writing isn’t so incredibly lucid that everyone is still with me.

For that matter, does anyone have a better way?