Salesforce, you’re not there yet!

What does the perfect CRM for your company look like?  At FindWAtt, we chose Salesforce because it makes the most use of attributes, and is the most customizable.  On the surface, Salesforce seems like the perfect tool for a company as attribute-crazy as we are.  We can create our own custom attributes and values (albeit with some limitations), use formulas to derive values, and create a series of rules to assign tasks to the appropriate person.

The problem is that while conceptually solid, the usability suffers from what seems to be an insufficient amount of structure. Each entity in Salesforce, whether it is Leads, Contacts, Opportunities or Accounts, has their own unique set of fields. I can create a new field for a Lead, but when that Lead is converted into an Opportunity, that new field does not go with it.  To make that happen, I have to dig into the settings, recreate the attribute (under Opportunities this time, instead of Leads) and then specify how those values should map.

Email to Salesforce is another feature that seems very useful, but  falls short of its potential.  Any email sent to a Lead (or Contact) can be Bcc’d to Salesforce and logged under that person’s record. This is very handy for organizing all of your correspondence.  Unfortunately, Salesforce can only match based on ONE of the recipient’s email addresses. If your lead or contact uses more than one email address, you’re out of luck! I know it sounds crazy that someone might actually have more than one email address, but allowing multiple values for any attribute (known as multiple cardinality) is a fundamental thing.

In my dreams I have the option of allowing multiple cardinality for any attribute, and the ability to add any custom field to any entity with the simple click of a button—but Salesforce has yet to make my dreams come true.

I mentioned in an earlier post (Amazon as a Benchmark) how much I both love Amazon and yet find it frustrating because of poor Findability .

I experienced poor Findability (and therefore this new term “web stress”) last week on Amazon as I tried to look for a desktop computer for my colleague Dan Barbata. Dan had been looking forward excitedly to a new computer he’d ordered from Dell about 3 weeks ago but for some mysterious reason Dell cancelled the order – something to do with a parts shortage. Some instant yet painless gratification seemed appropriate and as I’m an Amazon Prime member I thought I’d see what we could get by the end of the week.

Dan’s key criteria are 8GB RAM and a 64-bit CPU to make use of the RAM so he can have lots and lots of applications open at the same time without bringing his computer to a crawl (a problem with 32-bit computers because they couldn’t use more than 4 GB RAM).

First Search Attempt on Amazon

I go to Amazon, search for “Desktop Computer” and quickly navigate to the Desktop Category.

Amazon has lots of filters (a.k.a. facets or attributes) to refine my search:

• Operating System
• Included RAM
• Condition (New, Refurbished, etc.)
• Shipping Option
• Brand
• CPU Speed
• Hard Disk Size
• Average Customer Review
• Green?
• Price
• Seller

RAM is my first criterion but the filter choices provided are useless – the maximum range is 1 to 249 GB which is going to produce one thousand one hundred and forty-nine (1,149) results! Not exactly useful plus how many people nowadays are going to buy a Desktop with less than 1 GB of RAM?

I think it must be 20 years since I had a computer with less than 40 MB of RAM so either Amazon is selling an antique in the above 1-39 MB range or there’s a product data error – of course it’s a product data error:

Note this is a product that Amazon is selling itself and not one sold by an independent merchant through Amazon marketplace where you might think that data quality would be worse.

Second Search Attempt on Amazon

Ok, so now I’m forced to go back up to the search box and try again, this time searching for “8 GB RAM” while staying in the Desktop category. I filter the results by Windows 7 Home Premium and Hewlett-Packard (let’s give them a try after Dell) and Amazon returns 5 results, all of which are sold by Amazon MarketPlace sellers. Notice the reason these show up in the search – MarketPlace sellers put a phenomenal amount of product information into the title – apparently Amazon does not search Technical Details in the full product description which in turn explains why no computers sold by Amazon show up.

Third Search Attempt on Amazon

I don’t give up but only because I’m already thinking of writing this post. I cancel my 8GB search, filter by Hewlett-Packard and Windows 7 Home Premium and click on the products to get to the product description page, scroll down to Technical Details (what a pain) to find the RAM. After 4 or 5 tries, I eventually find a Hewlett-Packard computer sold by Amazon that could be delivered by week’s end. But I’m not going to suggest buying from Amazon to Dan because there’s no way we can compare the features of all the computers they stock that have the basic criteria (8 GB RAM, 64-bit CPU) – we simply can’t find them.

Search & Navigation and Product Data - Why doesn’t Amazon do a better job?

This incident is not a one off – I frequently experience problems with Amazon’s Search & Navigation and Product Data and it mystifies me why this should be the case with the largest and most successful Internet retailer. In this case they clearly have RAM as a separate attribute in a structured field – albeit with some data errors – but the ranges are messed up. In other cases I’ve seen key criteria “just sitting there” in semi-structured form (i.e. contained in text in a bullet point under Technical Details) that are not even addressed in product filters (a.k.a. faceted navigation). What’s particularly intriguing (frustrating from a consumer perspective) is why terms in the search box are not being run against structured values. For example if RAM is a separate attribute in a structured field, this presumably means that the value “8 GB” is associated with the HP Pavilion P6320F computer that I eventually found. In which case why did this computer not show up when I searched for “8 GB RAM?” And why is Amazon missing the key attribute of “64-bit?” Admittedly it’s only been a year or two that such computers have been available but they’re pretty common now and 64-bit is a mandatory requirement now for anyone who’s in the market for a high performance computer with lots of memory. Even if “64-bit” is not part of any structured data provided by the manufacturer, it’s a trivial text mining job to pull it out.

Perhaps I’m being overly tough on Amazon. When we see Findabilty problems on small to mid-size retailer’s sites, we tell them about them and only write about what we’ve seen in a disguised form. But I think Amazon is fair game because they really ought to be top of the heap. The really big driver of this post though is that Amazon is my primary online store and they’re giving me lots of unnecessary web stress.

Customers get stressed if you make them work harder than they should have to on your website and your performance metrics such as bounce rate and conversion rate will suffer.

CA (formerly Computer Associates) recently commissioned a study Web Stress – A Wake Up Call for European Business in which 13 volunteers wore skull caps to track their brain waves as they tried to search for and purchase a laptop PC and travel insurance. The study was conducted in Scotland by British usability experts Foviance. See some highlights here:

Brain wave analysis indicated that shoppers had to concentrate up to 50% more when using poorly performing websites, leading to greater agitation and stress.

It’s a given that when customers get frustrated they give up or go elsewhere – CA’s own (2009) estimates are that poor performance leads 40% of people to go to a competitor’s site and another 37% to give up entirely. What’s fantastic and exciting about the notion of tracking web stress is that this type of research gets us on the road to being able to measure usability; i.e. as well as experimenting with usability changes and their impact on conversion rates we’ll be able to:

1. Put an actual number on a website’s usability using an index or score.
2. Measure the impact on this Usability Index of making specific changes (e.g. improving Findability , changing design, streamlining checkout process).
3. Most excitingly, to create industry wide metrics that indicate the relationship between the usability index and performance metrics such as conversion rate. These metrics can then provide rule-of-thumb estimates as to how much an ecommerce site’s conversion rate is being held down by poor usability and what kind of improvement could be achieved if the site could move into the usability sweet spot.
   • My own guess is that the relationship between usability and website performance is something like an S-curve. Wouldn’t it be great if a retailer could find out they were at position A and by moving to position B they’d double their conversion rate?

   

   • This isn’t the whole story to conversion rate of course (other factors come into play) but adding this kind of knowledge to industry wisdom would help us all in a big way.

Amazon has emerged as the 800–lb gorilla of E-Commerce and some pundits believe that smaller retailers will get squashed in the expected slugfest between Amazon and Walmart. Based on my own experience with Amazon, however, I’m not at all sure.

I LOVE Amazon and buy everything I can there. Often, as is increasingly the case with many shoppers, I’ll go straight to Amazon and search for what I want before – or without -trying anywhere else. I’m an Amazon Prime member and 2–day free shipping is fabulous – especially when shipping from another retailer costs an arm and a leg. On average I buy something from Amazon once per week – last year I spent a little over $3000.

On the other hand, Amazon constantly drives me nuts because their Findability in some areas – particularly electronics and computers is annoyingly poor. It’s OK if you know exactly what you want but if you need to look at and understand alternatives, choosing the right product on Amazon can be a real pain because the attributes you need to narrow your selection are just not there.

Perhaps Amazon’s failure to provide attributes of significant depth in many categories is due to product data problems – like Comparative Search Engines, a lot of data is provided by independent merchants. Whatever the reason, Amazon loses a fair chunk of my business – e.g. today I bought a set of toner cartridges for a color printer ($200) on another website (one I have never used before) because I wasn’t able to understand – or trust – the choices presented to me – and I wasn’t sure I had isolated all the relevant choices.

I’ll be posting more examples of Amazon’s pluses and minuses but, for now, the key takeaway is that while Amazon is definitely the 800–lb gorilla there’s plenty of room for savvy merchants to hold their own.

The 3 key processes that determine whether your customers can find what they want

Have you ever been shopping in a grocery store, and one of the store employees politely asks, “Are you finding everything ok?” If you are like me and don’t know the layout of the store like the back of your hand, you take the opportunity to ask the clerk exactly where everything on your list is located. Otherwise you end up wandering up and down each aisle, looking at the shelves, hoping to find stuff. This is the basic concept behind findability: How easy is it to find what you are looking for? And in most grocery stores, I have found the findability to be very poor.

In his book “Ambient Findability” Peter Morville defines Findability, dictionary style:

find-a-bil-i-ty n

a. The quality of being locatable or navigable

b. The degree to which a particular object is easy to discover or locate

c. The degree to which a system or environment supports navigation and retrieval

On the web, and specifically for e-commerce sites, findability means how easy is it for a shopper to find the product they are looking for.

This is extremely well put, and I can’t say it more clearly. For e-retailers, having a website where the products are findable is critical to their ability to compete. If findability is poor, sales and customers are lost because…You Can’t Buy What You Can’t Find!

But how do you judge findability? There are three basic processes to be evaluated:

1. If you know what you want, can you find it? – This is called known-item-search, and appropriately, the search box is most often used. If I am looking for an 8 GB iPhone 3G, and I search using that exact phrase, do I get those results right away? Or are the first results something unexpected, like accessories for the phone? Or nothing at all?

2. If you have some idea of what you want, but do not know exactly, can you find it? –This is where findability is actually most difficult to achieve. You know you want a coffee maker, but which kind? Ideally you have some knowledge of coffee makers and which kind you prefer. But it may be you don’t have a clue. How well can you find the right coffee maker for your situation?

3. If you’re just browsing, will you easily discover something you want to buy? – In this situation, you are not focused on specific product type. But can you navigate through all the available choices? And to what extent can you refine your search.

This evaluation is far from academic. Findability has real business consequences. If you can find something easily, you have more time to decide whether to buy, and continue shopping for more. For the e-retailer and shopper alike, there is nothing worse than not being able to find the product they might buy. And worse, frustration in finding a product causes disillusion, preventing a transaction, and possibly losing a customer.

Will Evans, founder and Principal User Architect for Semantic Foundry, sums it up nicely, saying:

Increased findability leads to increased business results

• More people find what they’re looking for – faster – thus improving conversion rate
• Increased customer satisfaction and loyalty
• Decreased customer service cost

Opportunities for targeted merchandising

• Up-selling based on selected facets (similar attributes might mean affinities in the customers mind
• Cross-selling based on selected facets
• Each facet selected is valuable customer data (these are attributes customers are saying they are interested in!)

Have you shopped on your own site lately? Try each of the 3 findability processes. Even with known-item search, we find that lots of sites have problems. If you start with only a one or two keyword search, are you presenting your customer with pages and pages of products with no way to filter other than brand and price? Are you forcing your customer to keep adding keywords to the search box before they can get down to a manageable number? Or worse, does your search end up with fewer results than customers would get if they navigated to the relevant subcategory (a common problem)?

This will give you a rough sense of your site’s findability. To start managing your site’s findability, use the Findability Evaluation Framework available in our Findability Review section to identify where you can get the biggest Findability boost with the least effort. Or sign up for a FREE Findability Review, and we’ll do the work for you.

Have you ever had difficulty choosing a product when shopping online? Too many websites provide a large list of products and leave you with very few options for narrowing it down and no guidance at all as to what you should choose. To combat this problem, Easy2 Technologies has come up with their Product Selector, which claims to “help your customers find the right product to purchase, based on their unique needs and preferences.” But how well does it work? To find out, I used the demos on their site (http://www.easy2.com/site2009/productSelectors.aspx) to choose a sewing machine and a light bulb.

How to Use the Product Selector

The Product Selector consists of two main sections:

1) A list of questions to answer

2) The list of products that fit the answers to those questions

Operation is simple. Just answer the questions of your choice, and watch the list of products refine by your specifications. Answering a few questions quickly brings you to a manageable list of products to choose from.

The Pros

• All Optional Questions – You can answer the questions of your choice, in the order of your choice. Skipping questions is easy and intuitive.
• Multiple Choice Answers – Some questions allow multiple choices, so you’re not locked into only one answer.

• Real-Time Filtering – The list of products is filtered in real time as you answer each question, so you can easily see the results of your choices and re-evaluate if no results are found. (This is in stark contrast to some other sites, where you make a series of choices and then press “go”, only to get no products and no clues as to which combination of choices led to this result.)
• Real-Time Answer Updates – As you answer questions, the possible answers to remaining questions are updated appropriately. For Example, once you choose “serger” as the type of sewing machine, the product features that are not relevant for sergers are removed from the options for “What other features are important to you in a sewing machine?”

The Cons

• Missing Multiple Choice Answers – Some questions that should allow multiple answers do not. For example, “What is your price range?” allows only one choice, so if your actual price range doesn’t fit into their predetermined buckets, you’ll have to go through the selection process more than once.

• No Visual Breadcrumbs – When answering each question, you cannot see the answers you have given for other questions (although there is an indication of which questions have been answered).

• No Real-Time Question Updates – Questions are displayed after they become irrelevant. For example, after choosing “serger” for type of machine, the question “For making buttonholes, which do you prefer?” is still shown, despite the fact that none of the answers can be chosen, since sergers do not make buttonholes.

• No Help for Making Choices – No guidance is given on what choices you should make, so you must have domain specific knowledge or know exactly what you are looking for. For example, one of the questions for choosing a sewing machine asks about “special presser feet”, but does not explain what any of them do or why you would want one.

• Missing Questions – Some relevant questions are missing. For example, when choosing a lightbulb, there is no question about base type, so you can’t look at all bulbs for ceiling fans, appliances, etc.

• No Indication of Number of Results – There is no indication of how many results will be returned based on the answer to any question. This number is useful for guiding your choices, as you may choose not to click on an answer that will return too few results.

Conclusion

The Product Selector performs well in quickly narrowing down a long list of products, assuming you already know something about the category and what you’re looking for in particular. By answering 4 questions, I was able to narrow down a list of sewing machines from 39 to 5, making it much easier to compare them and make a choice.

Where it falls short is in offering a truly guided experience—it gives you options in the form of questions, but never provides information about what these options mean or why you should choose one over another.

The typical faceted navigation experience is one where the user is selecting product attributes. In this case, Easy 2 Technologies has transformed difficult-to-understand attributes into clear questions about user benefit; so instead of asking for 100W vs. 400W, they ask Regular Light or Brisk Light. This is an indicator of how people will shop online in the future, and despite a few shortcomings, Easy2 Technologies has a winner.

iStockphoto is an incredible source of images – over 4 million to choose from! Unfortunately, finding exactly the right image is worse than looking for a needle in a haystack. My first experience on iStockphoto was an amazing and extreme example of the desperate need for structured and attributed product data to aid customers in shopping.

With such a huge inventory of products (if you think of each image as a product), I was sure they’d have some way to narrow my selection. After all, I didn’t want to get stuck paging through 20 pages of images…next, next, next.

But that is exactly what ended up happening. I was looking for a picture of someone who was looking lost, so I typed in “lost.” I got back 362 pages and 10,858 results. Two categories were presented to “clarify my search.”

• Lost (Descriptive Position)
• Confusion

I could have used both metaphors for the way people tend to feel when shopping at sites like this, but I chose Confusion. Now I was down to…531 pages and 15,928 results! By being “clearer” I got 5,000 more results. The only way to further narrow my search were checkboxes labeled “photos,” “illustrations,” “flash,” “video,” and “audio.” I chose “photos” and “illustrations” and was left with virtually the same number of items.

At this point I felt stuck. I had some idea of what I wanted, but didn’t know how to find it. I knew two things:

1. I didn’t want a photograph of a person

2. I wanted the image to be blue (to keep with the theme of our site).

But I didn’t know what keyword search would produce my desired results.

Furthermore, I didn’t know what additional aspects of these images I should be considering. Simply put, I had no filters on the sidebar. I didn’t have the ability to filter on color, image type, or anything else. I had to go back to the search box, type different combinations of words, and hope to hit on the right set of images.

I found a few candidate images, but didn’t pull the trigger, because I wasn’t confident I had seen all of the choices. I wasn’t being guided through the experience. I felt like saying “Just give me the 40 images that fit my criteria, and let me decide!” But because iStockphoto did not have faceted search and navigation, this was not possible.

Without faceted navigation, or the ability to refine your search, the shopping experience is frustrating and painful. In my case, I didn’t end up buying anything because you can’t buy what you can’t find!