Ahalogy Liftwords Tool

Pinterest SEO Optimization

Project Overview

Ahalogy is continuing the expansion of its Pinterest marketing tools with the launch of Liftwords, a new technology that looks to help marketers boost their presence on the image sharing site by adding specific keywords to add to their pinned content.

Ahalogy's SEO tool suggests keywords as you compose Pin Descriptions to help increase your content's discoverability through search by 15% and allows you to schedule Pins at the optimum time of day with our auto-publishing feature.
Year
2014
Role
UX Designer
Methods & tools
Interviews, Wireframes, User Testing - Sketch, InVision
Platform
Web Browser Plug-In
Deliverables
Wireframe and Hi-Fidelity Prototypes

Design Process

The design process - illustrated below - that I implemented working with Ahalogy allowed me to effectively understand user needs while quickly creating concepts and validating those designs.

Discovery

Persona Profiles

Initial research started with me interviewing 5 Ahalogy employees that were Pinners on behalf of large brand clients to find out how they worked with current tools. In the interviews, I asked them to recall and walk me through the experience when they first used it and created a new project. I asked how they typically learn a new tool and how they expect to learn this tool.
From my research I understood that the tool I was designing need to help two major types of customers excel on Pinterest: large iconic brands (the P&G and Kellogg’s brands of the world) and high-end independent influencers (whether a single mom blogging in her spare bedroom or a small remote team running it like a business).

Problem Definition

How do we present these in our pinning UI in such a way that it’s intuitive what’s going on, and yet simple to perform? Intuitive because they quickly need to understand and trust the value of why we’re making these recommendations, and simple because pinning for a media property can often be a rote affair.
research & discovery

Data Science

Data science team set out to understand how certain words colocating together in a pin’s description could increase the likelihood of it getting re-pins or clicks by being found in search. They constructed a project and ultimately created these links between words that we know to help move these key ratios. Given access to this tool, I explored the functionality and what the system limitations were.
Concept

Idea Exploration

With an understanding of the technology, I started the process by sketching concepts for the UI. Concept One illustrates a contextual menu....In Concept Two, I explored a horizontal layout design with a menu that slides down. As the key word is selected, the list of words dynamically updates accordingly.
Design

Concept Iterations

This is where, once an image has been selected, the pin’s description, the board to which it’s pinned, and the schedule when it’s pinned are entered into the form. Selection of keywords would happen here.

I created five iterations of Concept One, going through designs that would be the appropriate level of interactions...
validation

Design Validation

Meeting with the business, engineering and the pinners, I presented the five UI concepts to highlighting strengths and weaknesses, and getting their feedback as users of the tool.
User feedback
I used the design review feedback to guide design decisions through the project.
design

Refinement

With the concept validated by the key stakeholders, I refined the design further in preparation of building a prototype that would showcase the tool in context of the environment that it would be used in.
design

Validation

With the feedback, I selected version 5 to develop into a click prototype in the context of using it on a blog and present it to users for further validation and refinement.
design & validate

Prototype Testing

As a user browses a blog the desired image can be captured and description added. The prototype reflected this and the key word optimization the actual technology would provide.

Results

The concept design and prototype lead to the development and implementation of the tool by engineers becoming a product within Ahalogy's portfolio of software and services offering. The tool increases discoverability by an average of 15%.