Why did we do this project in the first place?

I often find that when you work with a single business stakeholder things can be clean, neat, well thought out and align with the main goals. If everything isn’t dialed in, it is usually pretty easy to get the conversation on track and get things focused. The Challenge happens when you have a room full of business stakeholders. You’ll find that things aren’t always so clean because the solution that works for one part of the business doesn’t always work for another. The more departments that get involved, the more your goals get diluted and the more flexible your solution will have to be. Now throw a global, direct to consumer business in the mix and you are almost always going to have to make exceptions and build the system to the lowest common denominator, or build completely different systems across the regions. In these instances, you need to make sure you clearly define the purpose of a project and the goals of that project before you embark so you can keep everyone focused and limit the amount of time spent spinning on the project. When you do get a chance to work with the stakeholders, make sure that every request that they make or every decision that they are going to make aligns back to the main objective of the project.

I had worked on a guided shopping tool for a brand that sells widgets. We had a great working relationship with the vendor of the guided shopping tool. They were going out of their way to accommodate our needs agreeing to all kinds of custom development and exceptions in the contact because they wanted to launch a large US based global brand. We worked with the business to identify how they wanted it to work and, although we were speaking to the customer using our internal categorizations, the system still made sense. We were able to associate products in groupings that made it a little easier for the customer to explore different styles of widgets. We worked through all of the development and launched a test environment so everyone could see the system work. As more and more business stakeholders saw the system work, I started to get more and more feedback that it wasn’t quite right so we went back to redefine the experience. The business stakeholders started to want the guided shopping experience to go from a system that would help new customers understand our product offering and find a style that they like, into a system that would allow the customer to browse every widget we offered, all 2,500 SKUs in one experience. I started to explain that a guided shopping tool wasn’t intended to do that. Guided shopping was intended to allow customers to align our product offering to their style through different means depending on the customer’s mind set. The product team manufactured products based off of categories by widget function. If customers shopped for widgets based off of these categories it would be no problem at all but most customers buy widgets based off of fashion and style as opposed to function. The eComm team was trying to make customer understand these groupings and they made no sense to the customer. Additionally, the widgets were all set up as mutually exclusive to these groups but customers didn’t look at them that way. Just because a widget has technologies in it that make it ideal for playing sports doesn’t mean that a couch potato wouldn’t want that widget because they like the way it looked on them when they jump in the truck to go pick up some burgers from the drive-through. There should be a differentiation between the categories that product teams build products to and the categories that marketing sells products by. On top of this, business wanted customers to be able to navigating through the experience by color which is not a sound strategy. If the customer wants to browse widgets by category, color, or any of the other filterable attributes that the product is categorized by in the online store they can just navigate through the online store.

The eComm needed to divide the product offering based off the profiles of the customers that were buying those widgets. If there are widgets that fall into multiple categories because different segments liked them then they should live in both. Then we needed to pick a categorization that each of those segments would align or relate to. As an example, if you pick cities or music genres or socio-economic labels that people can relate to and then put the widgets that fit that demographic into those categories your guided shopping experience would be doing what it was built for. So if your market research found that your customers associate themselves to being urban, suburban, country, small town, beach city, tropical beach…then you could categorize your product based off of how customers, who were new to your products pictured themselves. Or if your product markets more closely aligned with Rock, Country, Indie, Pop, Hip Hop, Classical…You could create groupings around those so when a user goes into the classical category it would list all of the widgets that our demographic research showed were purchased by the profile who listens to classical music.

Project managers should always challenge the business stakeholders to make sure that the right tools, strategies and projects are being implemented with the right goals and KPIs in mind. It is the project manager’s job to understand the tools and the end goal that the business is looking to achieve to make sure they align. PMs need to guide the business to get the best implementation possible from the technologies available otherwise you end up with a product that doesn’t meet the initial request.


What Do We Do With All This Data?

analyticsDo you have an analytics strategy? Analytics can help inform every web project, but only if you know what to look for. There is a huge difference between “analytics” and an “analyst’s report”. Far too many times they are used synonymously but the truth is, data ≠ analytics.

Data needs to be interpreted in order to become analytics and in order to do that, you need an analyst with some good insights. I have seen far too many reports that have interesting data, but there really isn’t any strategy or actionable insight that comes from the data. Data can be used for so much more than just determining if you are up or down over yesterday, last week, last month, last year… A component of analytics covers those details but data by itself does not tell the whole story. A good analyst will know what story needs to be told, they will figure out what information needs to be pulled and how to compile an accurate depiction of what is happening. Most of the time, there will be holes in the data, but a good analyst will look elsewhere to fill in the holes and come up with a conclusion based off of the data that they are able to pull. A good analyst will be able to collate data from multiple sources to support their conclusion, but a great analyst will adjust their conclusion when the data is pointing in a different direction. Analysts don’t always have to be right. The great ones will lead you in the right direction but come up with alternate recommendations if their initial thoughts are proven wrong by the data. Analysts will work with the business to understand what what Key Performance Indicators (KPIs) should be defined and then determine the best way to collect, parse or consolidate data to tell an accurate story of what is happening and how the business might be able to make adjustments to move the metrics in a favorable direction. You should include your analysts when you are in the planning phases of a project so they can define the KPIs and make sure the metrics that need to be measured are tagged.

The key to improving any web implementation is to make sure you have a good analytics strategy but even more so, a great analyst. Make sure your Calls to Action (CTAs) and KPIs are defined throughout the site. Identify the different paths that users can flow through the site and make sure you know what the KPIs on each of the major steps of the funnel are. In order to do this you will have to identify all of the functions that the website is serving for your organization; does it do web sales, marketing, establishing brand? Does it assist in sales and help recruit talent? Does it do all of this and more? Make sure that you define these functions and then define conversion funnels for each of these end goals. Different steps in the conversion funnels will have different purpose and different KPIs. Gary Angel has written a great white paper on this topic called “Functionalism”.

If you look at a typical eCommerce site you may see a sales funnel that looks like this:
Homepage>Category Listing Page>Sub-category Page>Product Detail Page>Shopping Cart>Shipping/Billing info page>Confirmation Page.

In the simplest form of a sales funnel that particular path would have 6 points at which a person can get distracted or leave the site. And that is the simplest form not including going back and forth between categories, adding product to cart, removing product from cart ect. In this 7 step sales funnel your end goals is a sale. That would make the conversion for this funnel a product sale. If you want to improve the sales in this funnel you can’t make a change to the second step and expect to see if your change was an improvement by looking at the sales results over the next few weeks. There are far too many variables at play within each step. Let’s say you are selling shorts in October. You want to increase sales; you have a hunch that if you that if you remove the sub categories you’ll improve sales. So in the original scenario the user goes from homepage>shorts>cargo shorts>blue 5 pocket cargo shorts>cart>checkout…

So you think it would be better to remove one step in the funnel and you do away with the subcategories and delete boardshorts, cargo shorts, walking shorts and compression shorts and lump all the shorts into one big shorts page with 80 different styles on it. In essence you go from a category that has 4 sub-categories that have 20 products each to 1 category with 80 products. If you make the change and your sales improve 5% over the next 2 weeks things went well, right? Maybe not; you can’t really tell by looking at the last step in the funnel. You may have had a decrease in the number of people that went from step 2 to step 3 in the sales funnel, but sales may have still gone up because you had an extraordinarily hot week in the middle of October. You may have negatively impacted sales even though sales went up. Know what your KPIs are for each step in your conversion funnel. Your analyst will be able to collect data specific to each step so you will be able to make assessments at each step. If they can help you improve every step by a couple of percentage points your final conversion rate will go up exponentially.

Additionally, an analyst will know how to segment and parse data to get a better understanding of how the KPIs are performing based off of a desired response and User Experience. I had worked on a project where we implemented heatmaps so we could see what people were clicking on and what they were looking at throughout the website. We implemented the system and started to collect the data. After a few weeks I pulled data to see how people were using a specific page and was happy to see that people were looking at the exact sections of the page that we had hoped. The page worked as designed! People we looking at the product data, spending time reading and interacting with the content and then they were clicking on the button to add to cart. About two weeks later I was sitting with an analyst who was talking about some major adjustments to that page because according to the analytics and heatmap, the page wasn’t serving its intended purpose. I disputed this because what I had seen showed that it was working; people look at content and then buy the product. She showed me that when you segment the users into people who purchase, people who bounce and people who continue on to search for something else, the page wasn’t actually working how we intended. A good analyst will be able to look past the initial data to make sure that they are telling the appropriate story.

Implementing an analytics strategy is tough, especially if your organization doesn’t really understand the intricacies of the different KPIs throughout a sight and don’t really understand what data they need and what reports will help them make improvements. A strong project manager should understand what kind of analytics strategy needs to be implemented and what type of skills an analyst should have to implement it. Building a project plan around implementing an analytics strategy can be tricky, but a strong PM will keep the main goals in mind and not let it get off track.