There’s also a small group of people who tend to be quieter about their expertise, perhaps because as independent practitioners or small business owners they’re not supported by the marketing budgets of large companies. These people survive on their reputation, which has been built steadily on a record of solid advice, honesty and neutrality. I’m now lucky enough to be part of this group – an informal network of experts in subjects as diverse as search for Sharepoint, intranet strategy and taxonomy management. Occasionally we collaborate on projects, often we recommend each other to our clients and it’s always hugely enjoyable to meet in person and discuss the latest trends and industry landscape. This informal network means Flax can offer more services to our clients – and if we can’t help, we probably know someone we trust who can.

So I’m very proud to announce that this group – the Search Network – are releasing a joint publication, Search Insights 2018. In this 70-page collection of essays you can learn how to research, procure, choose, budget, plan and run a search project in the best way for your business and your users.

Unlike some other industry reports, we’re not charging for this report, you won’t have to register or give us your email address, and it’s Creative Commons licensed so you can even redistribute it if you like (with attribution). There’s no sponsorship, no plotting of vendors on confusing trend diagrams, no marketing buzzwords or direct recommendations – after all, we’re independent. We welcome any feedback you have of course.

My personal thanks to Martin White who has led this effort and who has also written about the Network and the report.

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The same problems remain however with making enterprise search work in practise: data locked in hard to access legacy systems, low-quality content and metadata, unrealistic expectations driven by over-optimistic marketing and most importantly the various people factors that affect all cross-departmental large-scale IT systems. No matter how clever the software, without the right people with the right training it’s very hard to deliver effective search.

It remains to be seen how the acquisition will change the enterprise search market – Elastic certainly have significant funding and admirable ambition – which in itself is probably enough to worry a few of Swiftype’s competitors.

The post Elastic acquires Swiftype and broadens its offering to include enterprise search appeared first on Flax.

Our intention was to combine our skills and experience, drawn both from academia and industry, and create something that would be useful for both those interested in researching enterprise search (perhaps for a PhD) and those developing actual search systems. Once you’ve read the book itself there are over 20 pages of references (derived both from academia and industry) to follow up. Hopefully the book will complement Martin White’s seminal Enterprise Search (Martin has kindly reviewed it for us here).

Huge thanks must go of course to my co-author Udo, Mark Sanderson at Now Publishing, those who reviewed early drafts including Martin White and David Hawking and all those who have provided help and information. The book will be available in printed form at the SIGIR 2017 conference in Tokyo and the publishers have also made the entire book available for free download until July 29th. We would of course be very grateful for any feedback! We’re also planning some joint presentations this autumn to introduce the book.

We’d also like to hope that our book goes a little way towards explaining what is still a much misunderstood, over-hyped and over-sold field – as Martin writes today.

The post Announcing our new book, Searching the Enterprise appeared first on Flax.

Let’s start with the definition, helpfully provided in another post from Forrester. Apparently ‘Cognitive search solutions are different because they: Scale to handle a multitude of data sources and types’. Every enterprise search engine promises to index a multiplicity of content both structured and unstructured, so I can’t see why this is anything new. Next we have ‘Employ artificial intelligence technologies….natural language processing (NLP) and machine learning’.  Again, NLP has been a feature of closed and open source enterprise search systems for years, be it for entity extraction, sentiment analysis or sentence parsing. Machine learning is a rising star but not always easy to apply to search problems. However I’m not convinced either of these are really ‘artificial intelligence’. Astonishingly, the last point is that Cognitive solutions ‘Enable developers to build search applications…provide SDKs, APIs, and/or visual design tools’. Every search engine needs user applications on top and has APIs of some kind, so this makes little sense to me.

Returning to the first article, we hear that indexing is ‘old fashioned’ (try building a search application without indexing – I’d love to know you’d manage that!) but luckily a group of closed-source search vendors have managed to ‘out-innovate’ the open source folks. We have the usual hackneyed ‘XX% of knowledge workers can’t find what they need’ phrases plus a sprinkling of ‘wouldn’t it be nice if everything worked like Siri or Amazon or Google’ (yes, it would, but comparing systems built on multi-billion-page Web indexes by Internet giants to enterprise search over at most a few million, non-curated, non-hyperlinked business documents is just silly – these are entirely different sets of problems). Again, we have mentions of basic NLP techniques like they’re something new and amazing.

The article mentions a group of closed source vendors who appear in Forrester’s Wave report, which like Gartner’s Magic Quadrant attempts to boil down what is in reality a very complex field into some overly simplistic graphics. Finishing with a quick dig at two open source companies (Elastic, who don’t really sell an enterprise search engine anyway, and Lucidworks whose Fusion 3 product really is a serious contender in this field, integrating Apache Spark for machine learning) it ignores the fact that open source search is developing at a furious rate – and there are machine learning features that actually work in practise being built and used by companies such as Bloomberg – and because they’re open source, these are available for anyone else to use.

To be honest It’s very difficult, if not impossible, to out-innovate thousands of developers across the world working in a collaborative manner. What we see in articles like the above is not analysis but marketing – a promise that shiny magic AI robots will solve your search problems, even if you don’t have a clear specification, an effective search team, clean and up-to-date content and all the many other things that are necessary to make search work well (to research this further read Martin’s books or the one I’m co-authoring at present – out later this year!). One should also bear in mind that marketing has to be paid for – and I’m pretty sure that the various closed-source vendors now providing downloads of Forrester’s report (because of course, they’re mentioned positively in it) don’t get to do so for free.

UPDATE: Martin has written three blog posts in response to both Gartner and Forrester’s recent reports which I urge you (and them) to read if you really want to know how new (or not) Cognitive Search is.

The post A lack of cognition and some fresh FUD from Forrester appeared first on Flax.

After a short break we continued with Tomasz Sobczak of Findwise (who had travelled from Poland especially to speak) on query completion strategies – you’ll have seen this feature where a search system suggests endings for the query you’ve begun to type. He described the various applications of this (including completing place names in map searches and available products in e-commerce) and described the many ways it can be implemented in Solr: facet.prefix, facet.contains, using N-grams, Shingles, the Suggester component, queries using synonyms and the Terms component. He noted the various pros and cons of each approach including how they may affect performance and suggested how a separate Solr index might be used purely for query completion. Data for query completion should also be clean and secure (you don’t want to show something the user isn’t allowed to know exists via query completion!). He finished with an example from Findwise’s work for Ericsson.

After the talks we had a brief discussion around how some of the less exciting features of Solr might be improved (we’ve blogged about our search for sponsorship for fixing some of these issues) and the suggestion arose that we might run some more Solr hackdays, in London or even the U.S.A. We’ll be looking into this possibility.

Thanks to our hosts, speakers and indeed everyone who came – see you next time!

The post London Lucene Solr Meetup – Enterprising attitudes to open source search & query completion strategies appeared first on Flax.

1. How to get started on improving Site Search Relevancy
2. A suggested approach to running a Site Search Tuning Workshop
3. Auditing your site search performance
4. Developing ongoing search tuning processes
5. Measuring search relevance scores

You know your search experience isn’t working – your customers, your colleagues, your bosses are telling you – you know you need to fix it, fix something but where do you start?

Understanding and improving search relevancy can often feel like a never ending journey and it’s true – tuning search is not a one-off hit – it’s an iterative ongoing process that needs investment. But the resources, companies and tools needed to support you are available.

Here, I’ll take a quick look at how to get started on your search tuning journey. I’ll be following up in subsequent blog posts with more details of each step.

Getting Started

Like any project, to be successful you need to understand what you want to achieve. The best way is to kick off the process with a multi-functional Search Workshop.

Typically ran over 2 days, this workshop is designed to identify what to focus on and how. It becomes the key to developing ongoing search tuning processes and driving collaborative working across teams.

Workshop Agenda

Whilst the agenda can be adapted to be specific to your organisation, in the main there are 4 key stages to it:

1. Audit
2. Define
3. Testing Approach
4. Summary

1. Audit – Where are we are now?

Spend time understanding in depth what the issues are. There are many sources of information you can call on:

• Web Analytics – How are queries performing today?
• Customer Feedback – What are the key areas that your customers complain about?
• Known Areas of Improvement – What’s already on your product backlog?
• Competitive Review – Very important for eCommerce sites – how are your competitors responding to your customers queries?

2. Define – Where do we want to be?

As a team agree what the objectives for the project are:

• What are the issues you want to address?
• Are there specific types of search queries you want to focus on?
• Is a overhaul of all search queries something you want to achieve?
• What are the technical opportunities you haven’t yet exploited?

3. Testing Approach – What’s the plan of attack?

This is the time to plan out what changes you will make and what methodology for testing and deployment you are going to use.

• What order should you make your configuration changes in?
• Are there any constraints / limitations you need to plan around?
• What resources do you need to support search configuration testing?
• How are you going to measure and track your changes so you know they are successful?
• Do you need to build in a communication plan for stakeholders?

4. Summary

Ensure that all actions are captured in a project plan with clear owners and timescales.

Workshop Attendees

Within an organisation multiple teams have responsibility for making search better, so at a minimum a subject matter expert from each team should attend.

Key attendees:

• Business Owner
• Search Developer
• Content Owner
• Web Analyst

Benefits of the workshop

There are practical and cultural benefits to approaching search in this way:

• Collaborative working practices across the different disciplines are improved
• Shared objectives and issues leads to better engagement and understanding of the approach
• A test and learn approach can be developed with the time between testing iterations reduced
• The workshop itself is an indicator to the wider business that search is now a key strategic priority and that it is getting the love and attention it needs

In my next blog I’ll cover how to run the workshop in more detail.

Karen Renshaw is an independent On Site Search consultant and an associate of Flax. Karen was previously Head of On Site Search at RS Components, the world’s largest electronic component distributor.

Flax can offer a range of consulting, training and support, provide tools for test-driven relevancy tuning and we also run Search Workshops. If you need advice or help please get in touch.

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The post Elasticsearch for Westcoast – why search is never simple! appeared first on Flax.

The search idea

So you’ve got this idea and you’re convinced that you need search as part of the puzzle, but you’re not sure where it fits, whether it will be performant or how to gather and transform your data so it’s ready for searching. Perhaps you’re from a startup, or maybe part of a skunkworks projects in a larger organisation. What you need is someone who really understands search software and what can be done with it to sit with you for a day or two, validate your technical choices, help you understand how to shape your data, even play with some basic indexing.

The proof of concept

You’re a little further along – you know what technology you’ll be using and you have some data all ready for indexing. However, before your funders or boss will release more budget you need to build something they can see (and search) – you’ll need an indexer and a basic search application. You could do it yourself but time is limited and you’ve not built a search application before. You’re expecting to spend a week or two developing something to show others, that lets them search real data and see real results. You might also want to experiment with scale – see what happens to performance when you add a few million items to the index, even if the schema isn’t quite right yet.

The big one

You’re building the big one – indexing complex data or many millions of items, and/or for a huge user base. You need to be very sure your indexing pipeline is fast, scales well, copes with updates and can transform data from many sources. You need to develop the very best search schema. Your search architecture must be resilient, cope with heavy load, failover cleanly and give the correct results. You’re assembling a team to build it but you need specialist help from people who have built this kind of system at scale before.

The migration

Finally you’ve secured budget to move away from the slow and innacurate search engine that everyone hates! Search really does suck, but you now have a chance to make it better. However, although you know how to keep the old engine running you don’t have much experience of open source search. Even though the old engine isn’t great, you’re doing a lot of business with it and you want to be confident that relevance is as good (and hopefully better) with the new engine – maybe you want to develop a testing framework?

We’re also increasingly delivering training (both for business users who want to know the capabilities of open source search and for technical users who want to improve their knowledge – we can tailor this to your requirements) and ongoing support – but everything starts with a search project of some kind!

The post The four types of open source search project appeared first on Flax.

We’ve been working recently with a couple of clients who sell significant volumes of products via their websites: in both cases the current search solution is underperforming. In this situation it’s far easier to justify an investment in better search: if customers can’t find products they simply won’t be buying them. Simple changes to the search algorithms can have huge impacts, costing or saving the company millions in revenue. However, installing a new search engine is just the beginning – it’s vital to consider a solid test strategy. To start with, the new engine should be at least as good as the old one in terms of relevance. The search logs will show what terms your users have typed into the search box, and these can be used to construct a set of queries that can be tested against both engines, with the results being scored by content experts, beta testers and even small groups of real customers. The results of this scoring can be used to inform how the new engine can be tuned – and of course, this should be an ongoing process, as search should never be built as a ‘fire and forget’ project.

There’s sadly little available on the subject of real-world relevance testing, although there’s a forthcoming book by Doug Turnbull and and John Berryman. Based on our work with the clients above, we hope later this year to be able to talk further about relevance testing and tuning – and how to do it right for e-commerce, avoiding significant financial risk.

UPDATE: Doug has been kind enough to give our readers a discount code for his book – “39turnbull” – not sure how long this will last but it gives you 39% off the price so worth a try!

The post When bad search hurts: finding that elusive ROI appeared first on Flax.

Andreas Hallgren of Chalmers University showed the evolution of their site-wide search facility, now based on Apache Solr. Unsurprisingly one of the main problems was determining who ‘owns’ search in their organisation: at least now they have a staff member who dedicates 25% of their time to improving search. He had some interesting points about the seasonality of academic searches and how analytics can be used to ‘measure more, guess less’. I was up next talking about Search Turned Upside Down, using a similar set of slides to this one: thanks to all who came and asked some great questions.

Next was Helen Lippell who I have heard speak before on how to get Enterprise Search right – Helen had some great anecdotes and guidance for an attentive audience. Ed Dale followed with five tips for great search: index the right content, optimise this content, measure search, make a great UI and listen to your users – I can only agree! He also characterised the different kinds of content including the worrying ‘content we think we have but we don’t’. The last presentation I attended was by Anders Quitzau of IBM on their fascinating Watson technology: sadly this was a rather marketing-heavy set of slides, with plenty of newly minted buzzwords such as Cognitive Computing and very little useful detail.

Thanks to Kurt Kragh Sorenson and Kristian Norling for inviting me to speak and attend the conference, next time I hope to see a little more of the event!

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