• FAQs

          Search engine optimization (SEO) helps businesses drive visits to their website through organic search traffic. Given that the top organic search results receive a third of the clicks, a decline in ranking could be detrimental for your business. Implementing SEO best practices on your website will help to ensure that your web content is seen by as many potential customers as possible. The more visitors you have, the better your chances are of converting those visits into sales!

          Local search engine optimization (SEO) helps local businesses gain visibility by optimizing their local business listings for local search. A business that leverages local SEO will include its address, phone number, local opening times, and exact location in the form of a local citation. The goal is to rank for local searches which are usually performed by people in a specific geographical region looking for a business near them.

          We typically see results within the first 30 to 60 days, but when it comes to SEO, there are many factors at play. It's important to remember that SEO is a long-term strategy and results may not come as fast at you wish.

        • FAQs

          Digital advertising uses the internet to send advertisements to customers who are online through different websites and social media platforms like Google, Bing, LinkedIn and Facebook.

          The price for Google Ads management depends on the monthly ad spend. For accounts with $1,000 in monthly ad spend, the price is $550/month. Between $1,000 and $5,000 a month in ad spend, the price is $950/month. For $5,000 to $10,000 a month in ad spend, the price is $2,000/month. For more than $10,000 a month in ad spend, the price is $4,500/month.

          The price for Social Media Ads management depends on the monthly ad spend. For accounts with $1,000 in monthly ad spend, the price is $550/month. Between $1,000 and $5,000 a month in ad spend, the price is $950/month. For $5,000 to $10,000 a month in ad spend, the price is $2,000/month. For more than $10,000 a month in ad spend, the price is $4,500/month.

        • FAQs

          This depends on the complexity and size of a redesign and if eCommerce is needed. On average, it takes around 14-18 weeks from the web design intensive stage to launch.

          If your website experiences the following issues: it’s not responsive on all devices, has a slow loading speed, the design appears old and tired, users don’t spend long on the site, sales are stagnant, or your business is going through a rebranding - your website needs a redesign to boost your brand awareness and sales.

          Sometimes there’s no need to rebuild a website. Minor edits, refreshing page content and images, or restructuring page layout for SEO best practices can boost traffic and sales.

        • FAQs

          Semantic search launched in 2013 with the release of Google's Hummingbird update. Since then, Google's search engine has become more complex. The integration of machine learning, with RankBrain, and NLP, with BERT, has enabled the search engine to better understand the context of a query and deliver more personalized and targeted results. Semantic SEO is the process of creating machine-readable content using structured data and linked open data to help search engines better understand your content.

          On-page SEO is the practice of optimizing individual web pages in order to rank higher and earn more relevant traffic in search engines. On-page SEO refers to both the content and HTML source code of a page that can be optimized, as opposed to off-page SEO which refers to links and other external signals. From meta tags to page content, website structure, and HTML, on-page optimization services are focused on making your website more visible to search engines.

          Structured data refers to any organized data that conforms to a certain format, such as information in a relational database. When information is highly structured and predictable, search engines can more easily organize and display it in creative ways. Structured data involves using a piece of code that is laid out in a specific format easily understood by search engines. The search engines read the code and use it to display search results in a more dynamic way.

        • FAQs

          An SEO agency has experts in different areas of search engine optimization that may be out of the realm of your marketing team's abilities. SEO can be very complex and time-consuming. Furthermore, as search engine algorithms change it can be difficult to stay current on the latest ranking factors and strategies for improving online visibility. You will likely see a greater return on investment and better results from using a professional SEO agency than you would from tackling this on your own.

          As a digital marketing agency, SMA Marketing provides products and services in four areas: SEO, Local SEO, Digital Advertising, and Web Design

          We focus on building authentic, long-lasting relationships with our clients. We’re goal oriented and results driven and believe in doing good and making a difference in the world.

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How to Run a Data-Backed Experiment

Experiments are powerful ways to validate your assumptions. By setting up your experiment to collect relevant KPI’s you and your business will get deeper insights that you can put into action. In this article, we will outline a step-by-step process for running a data-backed experiment.

The following outline is a paraphrase from chapter 8 in “Winning with Data” by Tomasz Tunguz and Frank Bien. Anyone looking to build a data-centric culture should take a look at this book. The authors do an excellent job of showing the power of big data and how using this data can improve your business and culture. Ok, let’s get into the steps to building a data-backed experiment.

Step 1: Determine Actionability

Before ever running an experiment, you need to be sure that your outcomes will produce actionable insights. If your experiment doesn’t help you make better decisions, you may need to rethink whether or not this experiment is worth doing in the first place.

Step 2: Bookend Expected Results

After you have determined that the experiment is worth undertaking, the next step is to bookend expected results. Colin Zima, Chief Product Officer at Looker, explains, “This is one of the keys to ensure rigor around decision making.” An example from “Winning with Data” highlights Zendesk’s Net Promoters Scores. If the score falls below 50, the team investigates whether the sales team is over-promising in the sales process. This is one example of how a team bookends expected results to help them take action.

Step 3: Design the Experiment

When creating a statistical experiment, we need to develop a hypothesis. This gives us something to validate or invalidate. But, we also have to be careful of biases. When designing the experiment, be sure to allow room for “the devil’s advocate.” This will help ensure that the results are more accurate.

The experiment should be designed to collect as much data as needed to attain statistical significance. This will differ from company to company and experiment to experiment. To come to a conclusion that is statically relevant, you need to have enough data points.

For example, when we test whether or not a landing page is converting at a high enough rate, a sample of 10 users is not nearly enough. Typically we shoot for a minimum of 100. At this threshold, we start to have enough data to conclude whether or not the page is converting at a healthy rate.

For more in-depth experiments, you may also want to find the probability of your hypotheses or P-Value.  A P-Value is used in hypothesis testing to help you support or reject the null hypothesis. The P-Value is the evidence against a null hypothesis. The smaller the P-Value, the stronger the evidence that you should reject the null hypothesis. You can learn more about p-value here: http://www.statisticshowto.com/p-value/

You also may need to find the Z-score. The Z-score (aka, a standard score) indicates how many standard deviations an element is from the mean. You can calculate a Z-score from the following formula.

z = (X Рμ) / σ

Z is the Z-score, X is the value of the element, Œº is the population mean, and œÉ is the standard deviation.

While these formulas can seem overwhelming if you haven’t worked with statistics in a while, having a base understanding of them can help. There are some programs that help you figure out these numbers to predict outcomes better.

Step 4: Calculating Time to Run the Experiment

At this point, you should have a good understanding of what you want to solve and the sample size you will need to achieve statistical significance. Now, we need to calculate the time we will need to get the results we are looking to find. Again, different experiments will take varying amounts of time. But knowing what information you need and how long it will take to get, will help your team and business have proper expectations for the experiment.

Step 5:  Run the Experiment and Analyze Data

The final step is to put the experiment into motion.  Once we have collected the data, we must analyze the information and validate or invalidate our assumptions. Then we must take action on the data we uncovered.

This is a simple 5-step process to getting started with data-backed experiments. While the process is simple, it is very powerful and can help you and your business get the actionable data needed to make better decisions.

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