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Part of what makes the SEO business so risky is the fact that the search engines control everything, and we only have a decent idea of what goes into the ranking factors. While research, trial and error, and some clues from Matt Cutts have guided us along the way, there are plenty of less than reputable SEO companies out there lying to business owners who are none the wiser. Want to make sure you’re not getting swindled? Watch out for these.

Lie #1: “We Don’t Need Experience in Your Industry”

SEO agencies can work magic in industries they know, so look for a company that specializes in helping companies like yours. You can use an agency that doesn’t have much of a clue about the kind of work you do and what your audience wants to hear, and they can do a good job based on your guidance and research, but it won’t have quite the same “oomph” to it.

Lie #2: “We Guarantee #1 Rank in Google”

Of course, there’s value in a #1 ranking and everyone wants to be there. After all, a 2013 study showed 91.5% of all traffic goes to page one, 4.8% goes to page two, and 1.1% goes to page three. But if you see/hear this one run and run fast in the other direction.

No SEO company can promise this to any client. In fact, the most reputable companies will outright admit they can’t guarantee results. Google warns against it, and since they’re the ones who practically run the show, listen to them—not the people who are trying to take your money.

Lie #3: “We can Fix Your SEO in a Month”

Ha! Even if you started using the Internet for the first time last year, you’ve no doubt seen tons of changes happen every day. SEO requires ongoing monitoring and adjustments to strategy based on what you see happening. Google is constantly updating their algorithms to better improve services for their customers, as we’ve seen in the past with Penguin, Panda, and various other updates. Moz shares an algorithm change history that provides more details about all the changes that have occurred, and when.

Lie #4: “Outreach is the Answer”

This is a tricky one, because for many industries it can be helpful. However, for some, say for instance, a kitchen and bath design company operating in a small local area, it doesn’t make sense. What good would it do to feature a business that can’t possibly have national reach on a major niche website like HGTV? Sure, it may get this business in front of thousands of eyes, but since that business owner can’t offer his services to all of them, his SEO budget is better spent on other strategies.

Lie #5: “Your Best Content Belongs on Your Website”

You always want to put your best foot forward, but sometimes it’s a good idea to use that stellar content on a niche website that will draw traffic (and hopefully revenue) to your own website.

Lie #6: “SEO is All You Need” Lie #7: “You Can’t Do it Yourself”

When hiring an SEO consultant or team to work on your website, do your homework. The second you hear one of these lies, it’s time to move on to another option. Now, is this an exhaustive list of the lies you could possibly hear? Not exactly. You’ll have to use your own judgment when making the final hire. One of the best ways you can verify company skill is to see where their own site ranks. SEO, just like any other industry, is highly competitive. If they can’t rank their own site well, what makes you think they’ll be able to rank yours?

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Can Seo Be Made Predictable?

3. Unintentional Collateral Damage During Optimization Efforts

A page has the potential to rank for multiple keywords.

Finding the balance between the right content, the right target keywords, and the right optimization efforts is a challenge.

As an SEO practitioner, the following scenarios may seem familiar to you:

A website will contain multiple pages covering the same topical theme, with external backlinks and target keywords distributed across these pages and the best-quality links not optimized for the right target keywords.

A site undergoes a rebuild or redesign that negatively impacts SEO.

Conflicts of interest arise between various business units when it comes to optimization priorities. Without a mechanism to identify which optimization efforts will have the greatest impact on search rankings and business outcomes, it is hard to make a business case for one optimization strategy over another.

4. The Unreliability of Standard CTR Benchmarks

The relative position of the URL on the SERP for a specific keyword.

The packs that are displayed (answer box, local pack, brand pack, etc.).

Display of thumbnails (images, videos, reviews, rating scores, etc.).

Brand association of the user to the brand.

Calculating CTR by rank position is just one measurement challenge.

The true business impact of SEO is also hard to capture, due to the difficulty identifying the conversion rate that a page will generate and the imputed value of each conversion.

Search professionals must have strong analytical skills to compute these metrics.

5. Inability to Build a Business Case for Further Investments into Data Science

When making investment decisions, business stakeholders want to understand the impact of individual initiatives on business outcomes.

If an initiative can be quantified, it is easier to get the necessary level of investment and prioritize the work.

The ROI of SEO can seem minimal to leadership when compared to the more predictable, measurable and immediate results produced by other channels.

A further complication is the investment and resources required to set up data science processes in-house to start solving for SEO predictability.

The skills, the people, the scoring models, the culture: the challenges are daunting.

Making SEO Predictable: The Need for Scoring Models

Now that we’ve established the path to predictability is one fraught with challenges, let us go back to my initial question.

Can SEO be made predictable?

Is there value in investing to make SEO predictability a reality?

The short answer: yes!

At iQuanti, our dedicated data science team has approached solving for SEO predictability in three steps:

Step 1: Define metrics that are indicative of SEO success and integrate comprehensive data from the best sources into a single warehouse.

Step 2: Reverse engineer Google’s search results by developing scoring models and machine learning algorithms for relevancy, authority, and accessibility signals.

Step 3: Use outputs from the algorithm to enable specific and actionable insights into page/site performance and develop simulative capabilities to enable testing a strategy (like adding a backlink or making a content change) before pushing to production – thus making SEO predictable.

Step 1: Identification of Critical Variables & Data Integration

As mentioned before, one of the major roadblocks to SEO success is the inability to integrate all necessary metrics in one place.

SEO teams use a myriad of tools and browser extensions to gather performance data – both their own, and comparative/competitive data as well.

What most enterprise SEO platforms fail at, however, is making all the SEO variables and metrics for any particular keyword or page accessible in one view.

This is the first and most critical step. And while it requires access to the various SEO tools and basic data warehousing capabilities, this essential first step is comparatively easier to bring to life in practice.

We haven’t yet entered the skill- and resource-heavy data modeling phase, but with the right data analytics team in place, the integration of data itself could prove to be a valuable first step toward SEO predictability.

How?

Let me explain with an example.

If you are able to bring together all SEO metrics for your URL chúng tôi with an understanding of the value of each metric, it becomes easy to build a simple comparative scoring model allowing you to benchmark your URL against the top-performing URLs in search. See below.

PRO TIPS: For text data (or content), consider a mix of the following variables:

Frequency of word usage.

Exact and partial matches of keywords.

Relevance metrics using TF-IDF, Word2Vec or GLoVe.

For link data, consider the:

Relevancy of the links to the target page.

Authority distribution of linking pages/domains.

Percentage of do-follow/no-follow links.

Automate this, and you have at your disposal, a reliable and continuous benchmarking process. Every time you implement changes toward optimization, you can actually see (and measure) the needle moving on SERPs.

Tracking your score and its components over a period of time can provide insights into the tactics deployed by competitors (e.g., whether they are improving page relevancy or aggressively building authority) and the corresponding counter-movements to ensure that your site is consistently competing at a high level.

Step 2: Building Algorithmic Scoring Models

Search rankings reflect the collective effect of multiple variables all at once.

To understand the impact of any single variable on rankings, we should ensure that all other parameters are kept constant as this isolated variable changes.

Then, to arrive at a “score,” there are two ways to develop a modeling problem:

As a classification problem [good vs. not good]

In this approach, you need to label all top-10-ranked URLs (i.e., those on the first SERP) as 1 and the rest as 0 and try to understand/reverse engineer how different variables contribute to the URL being in the top page.

As a ranking problem

In this approach, the rank is considered as the continuous metric and the models understand the importance of variables to rank higher or lower.

Creating such an environment where we can identify the individual and collective effects of multiple variables requires a massive corpus of data.

While there are hundreds of variables that search engines take into consideration for ranking pages, they can broadly be classified into content (on-page), authority (off-page) and technical parameters.

I propose focusing on developing a scoring model that helps you assign and measure scores across these four elements:

1. Relevance Score

This score should review on-page content elements, including:

The relevance of the page’s main content when compared to the targeted search keyword.

How well the page’s content signals are communicated by marked-up elements of the page (e.g., title, H1, H2, image-alt-txt, meta description etc.).

2. Authority Score

This should capture the signals of authority, including:

The number of inbound links to the page.

The level of quality of sites that are providing these links.

The context in which these links are given.

If the context is relevant to the target page and the query.

3. Accessibility Score

This should capture all the technical parameters of the site that are required for a good experience – crawlability of the page, page load times, canonical tags, geo settings of the page, etc.

4. CTR Algorithm/Curve

The CTR depends on various factors like keyword demand, industry, whether the keyword is a brand name and the layout of the SERP (i.e., whether the SERP includes an answer box, videos, images, or news content.)

This makes it easier for the SEO program to monitor the most important keywords.

If you can compare these three sub-scores and underlying attributes, you would be able to clearly identify the reasons for the lack of performance – whether the target page is not relevant enough or whether the site does not have enough authority in the topic or if there is anything in the technical experience that is stopping the page from ranking.

It will also pinpoint the exact attributes that are causing this gap to provide specific actionable insights for content teams to address.

Step 3: Strategy & Simulation

An ideal system would go one step further to enable the development of an environment where SEO pros can not only uncover actionable insights, but also simulate proposed changes by assessing impact before actually implementing the changes in the live environment.

The ability to simulate changes and assess impact builds predictability into the results. The potential applications of such simulative capabilities are huge in an SEO program.

1. Predictability in Planning and Prioritization

Resources and budgets are always limited. Defining where to apply optimization efforts to get the best bang for your buck is a challenge.

A predictive model can calculate the gap between your pages and the top-ranking pages for all the keywords in your brand vertical.

The extent of this gap, the resources required to close it and the potential traffic that can be earned at various ranks can help prioritize your short-, medium- and long-term optimization efforts.

2. Predictability in Ranking and Traffic Through Content, Authority, and Accessibility Simulation

A content simulation module will allow for content changes to be simulated and the resulting improvement in relevance scores – as well as any potential gains in ranking – to be estimated.

With this kind of simulation tool, users can focus on improving poorly performing attributes and protect the page elements that are driving ranks and traffic.

A simulation environment could grant users the ability to test hypothetical optimization tactics (e.g., updated backlinks and technical parameters) and predict the impact of these changes.

SEO professionals could then make informed choices about which changes to implement to drive improvements in performance while protecting any existing high-performing page elements.

3. Predictability in the Business Impact of SEO Efforts

SEO professionals would be able to use the model to figure out whether their change is having any bottom-line impact.

Integrating this with website analytics and conversion rate data allows conversions to be tied to search ranking – thus forecasting the business impact of your SEO efforts in terms of conversions or revenue.

The Final Word

There is no one-size-fits-all when it comes to developing SEO scoring models. My attempt has been to give a high-level view of what is possible.

If you are able to capture data at its most granular level, you can aggregate it the way you want.

This is our experience at iQuanti: once you set out on this journey, you’ll have more questions, figure out new solutions, and develop new ways to use this data for your own use cases.

You may start with simple linear models but soon elevate their accuracy. You may consider non-linear models, ensembles of different models, models for different categories of keywords – high volume, long tail, by industry category, and so on.

Even if you are not able to build these algorithms, I still see value in this exercise.

If only a few SEO professionals get excited by the power of data to help build predictability, it can change the way we approach search optimization altogether.

You’ll start to bring in more data to your day-to-day SEO activities and begin thinking about SEO as a quantitative exercise — measurable, reportable, and predictable.

Measuring Seo Success – 3 Metrics You Aren’t Tracking But Should Be

Tracking all the usual metrics can help you measure SEO performance, but there are 3 other metrics you probably aren’t tracking that could help make a big difference

SEO is all about generating organic traffic to a website and ensuring that the acquired organic traffic converts well.

As an SEO professional, you’re probably already be tracking a number of metrics, such as organic traffic, bounce rate, conversion rate, keyword rankings, backlinks earned etc. But, there are three metrics that most SEOs aren’t tracking but they really should be.

Check out our Quick Win – 3 killer techniques to boost SEO

Here’s three simple methods to give your website a huge boost in Google rankings – helping you gain more traffic and grow your audience. Start making a difference today.

Access the Re-engineer your meta data to boost SEO success

Let’s learn what’s these three metrics are and how to track them:

1. Organic traffic ‘quality’

Organic traffic quality is a better metric to track than the number of organic visits. For example, you start doing SEO for a site that has 5,000 organic visits each month. You measure the organic traffic quality of the site and find that 30% of the organic site traffic is coming via bots or fake IP addresses. You share your findings with your SEO client that 30% of the traffic is of zero value. The actual people (real traffic) who are visiting the site are 3,500 and not 5,000.

After working for a quarter, you measure the increase in organic traffic and find that the traffic increased by 30%. But, you filtered out the spam traffic from the 30% increase and find that the real increase in traffic is around 20%. Hence, measuring traffic quality is more important as compared to organic traffic. Comparison of organic traffic should be done after filtering out the spam traffic. This is what every SEO should be doing.

Finteza is a great tool that lets you identify the percentage of quality traffic on a site. It is a buyer side analytics solution that shows real traffic data. It displays three levels of traffic coming to a site:

Green indicates pure traffic, yellow indicates traffic via proxy or VPNs and red indicates visits via spam IP addresses or hackers. This is what a sample traffic dashboard looks like. As you can see, you can easily filter the organic traffic and see the actual traffic coming to your website after ignoring spam traffic, VPNs and bots. This way, measuring SEO success becomes easier:

2. Mobile rankings

This report will display all the mobile rankings for the keywords you are currently tracking, allowing you to see what keywords you should focus on and how you can amend your startegy.

3. Total number of keywords under featured snippets

Getting a website featured under featured snippets is guaranteed to increase the amount of high-quality and relevant traffic coming to your site. This is the reason, you must measure the number of keywords that are ranking under featured snippets. This is a primary KPI that’s linked to branding and conversions.

[Image Source]

Increasing the number of keywords ranking under featured snippets can have an immediate impact on both the quality and quantity of organic traffic generated to your website.

Final thoughts

Measuring your SEO efforts is critical to its success. There are other metrics that you need to track other than the number of conversions happening on your site because tracking primary and secondary KPIs are essential to leave an impact on the actual number of conversions happening on your site. Start tracking these three new metrics in your SEO campaign and see the difference it brings to the overall ROI.

Web Recruitment: Don’t Just Post Jobs

Furthermore, Wheeler believes candidates will start to create electronic portfolios. For instance, software engineers could provide mini case studies of how they contributed to a project, outlining their role and the areas of implementation in which they participated. They could include snippets of code and procedures they created. “The concept here is to provide credible proof that they have a skill or did contribute to the project,” Wheeler says.

Scratching below the surface

Cisco’s Web site goes a step farther than Lucent’s with a feature called the Profiler, which bears the motto, “Because the best resume is no resume.”

THE SCREEN TEST

The Web is a good place to prescreen job applicants. Here are some suggestions for your site:

Remember the basics: name, contact information, employment history, education, languages spoken, job preferences, and career objectives.

Dig deeper into candidates’ employment history,asking which specific functional IT areas they’ve supported and which technical tools they use, as Cisco Systems Inc. does on its Web site.

Ask for a list of skill sets and competencies.Cisco, for example, asks applicants to choose from a list of skills such as, “partnerships,” “functional/cross-functional knowledge,” “ability to solve problems and make decisions,” and “dedication to customer success.”

Get references.

Ask for the following information:What characteristics do the candidate’s ideal job include, desired salary range, location, and cultural environment (small or large teams, structured or unstructured).

The Web is a good place to test rudimentary skills,like asking candidates to write samples of code.

Include open essay questions to really get a flavor for the candidate’s personality, such as, “The specification has just been changed, but your manager won’t allow you to extend your deadline. What would you do?”

Like a resume builder, the Profiler asks candidates about their education and employment history. Then it starts digging deeper with such questions as, “What functional areas in IS have you supported?” and, “What technical tools do you use?” and even, “Describe your experience in writing documentation for users.”

Candidates are also asked to choose from a list of competencies that best describe them. Choices include “industry knowledge,” “functional/cross functional knowledge,” and “solve problems and make decisions.”

Then candidates are asked to provide a list of their top 10 skill sets (such as TCP/IP or C++) and the amount of experience they’ve had with each. Finally, the site asks for references “to corroborate your story.”

With tools like the Profiler, companies stand a good chance of weeding out unqualified candidates as well as conducting a pretty thorough prescreening of viable applicants. And think of the time you save by receiving this information right away, rather than having to conduct a prescreening telephone call.

Going even further

chúng tôi delves even deeper into the prescreening process. First, when visitors go to the careers site–be they active or passive job candidates–they are asked for an e-mail address. They can also subscribe to information about the company, such as quarterly reports and job fairs, or ask to be notified when jobs come up that might be a good match for them.

Second, candidates are asked to describe their own characteristics and the traits of their ideal job, including their experience level, field of expertise, desired salary range, and location.

Meanwhile, hiring managers fill out the same information about the specific jobs they post. “And that’s the first step of matching,” says World.hire’s Miller. “We have a matching engine that’s constantly matching those characteristics.”

Once a match is made, candidates receive an e-mail that links them to the job description. If they want to apply, they answer a series of screening questions, which the hiring manager has specifically written for the particular job posting. These include true/false, multiple-choice, or open essay questions that the manager scans for certain key words. A scoring metric automatically filters out unlikely candidates and forwards the acceptable ones to the hiring manager.

Some questions deal with cultural fit, asking candidates which environment they prefer–small or large teams, structured or unstructured. Others might test rudimentary skills, like asking prospective employees to write Java code. In the end, hiring managers have practically completed a preliminary interview without opening their mouths.

The downside

Of course, there are lots of kinks to work out in this new world of Web-based recruiting. For one, I can see resume builders and lengthy prescreeners leading to application fatigue on the part of job seekers. Rather than typing up a short cover letter and attaching a resume, they’ll have to customize answers for each job.

On the other hand, “you’re allowing candidates to market themselves specifically to a job, as opposed to allowing hiring managers to pull out your qualifications from a static resume,” World.hire’s Miller says.

Also, I can see candidates becoming savvy enough to outsmart prescreening questions. For instance, companies might start asking similar questions for common job titles. If candidates see this, they could prepare their responses beforehand, thus losing the spontaneity and customized nature the company is seeking to capture.

Worse, unqualified candidates could preview the screening questions and do some basic research to find out what responses would be acceptable. “The way some of our customers are dealing with that is to change the questions on a regular basis,” Miller says.

Another way might be to throw in some unexpected questions to get a feel for candidates’ personalities, in addition to their capabilities. chúng tôi suggests including open essay questions. For instance, ask candidates how they would react in certain situations, such as “the specification has just been changed but your manager won’t allow you to extend your deadline.”

As Global Learning Systems’ Wheeler says, more organizations are bound to use these techniques more frequently over the next few years, adding in aptitude tests, personality tests, and more. “If you indicate that you can read and write French, you may be asked to do so on the spot as part of the screening process,” he says.

At the same time, “there is also no doubt that candidates will rebel, learn to evade the tests, develop techniques for using the computer to psych out the interrogating computer, and so forth,” Wheeler continues. That’s why, no matter how much you use your Web site to do recruiting for you, you can never eliminate the human touch. “In the end, it will always boil down to two things: people talking to people and results,” Wheeler says.

Mary Brandel is a freelance writer in Norfolk, Mass., specializing in business applications of technology. She can be reached at [email protected].

Don’t Let Backup Take A Backseat

With storage requirements moving into the tera-, peta- and exabyte ranges, companies need to refine their backup strategies to ensure availability of their growing data stores.

“Many data centers still perform backup operations the same they have for decades – and it does not work any more,” says Lauren Whitehouse, Analyst, Enterprise Strategy Group, Milford, MA. “It is time to re-evaluate the capabilities and requirements, and reset expectations – just because a 4GB Oracle database could be recovered in three hours in 1987 doesn’t mean it can be today when the database is 4TB.”

Accordingly, Enterprise IT Planet interviewed several storage experts and gleaned the following tips for improving your own backup and restoration procedures.

1. Plan in reverse – figure out what needs to be restored, and how fast, and then devise an appropriate backup plan.

“What people should do, but often don’t, is start with the recovery requirements,” says W. Curtis Preston, vice president of Framingham Mass. storage consultancy GlassHouse Technologies, Inc.

This means determining the Recovery Time Objective – how quickly the data needs to be restored – and Recovery Point Objective – how current the data must be – for each class of data and creating a plan that meets those requirements.

2. Save files to disk before migrating them to tape.

“Disk staging makes a huge difference, shrinking backup windows by as much as three quarters,” says Ramon Kagan, Manager of UNIX services at York University in Toronto. “We are able to do backups much faster from the server standpoint and then cycle it to tape during the day, saving people and servers a lot of time.”

3. Eliminate Excess – Do you need to store daily copies of a file that hasn’t changed in six months, or the personal copies of an email the CEO sent to all employees? Deduplicating files reduces the amount of storage needed and speeds backup times.

“We have commonly seen 20-to-1 capacity reduction using data de-duplication,” says Whitehouse.

4. Have backups stored outside the disaster impact zone. At a minimum, backup tapes should be stored off site. Better yet, all data is mirrored to a disaster recovery facility far enough away that it is still on line when the flood/hurricane/earthquake/blackout brings down the primary data center.

5. Track down and eliminate any network bottlenecks, which will slow down backup and restoration. This is particularly an issue with server virtualization, where multiple virtual servers are using the same network interface card and network connection.

“Make sure that you walk through the whole chain from client, to network, to server, to tape drive to ID bottlenecks,” says Preston. “You may be surprised to find that the bottleneck is Gb Ethernet to the tape drive. Tape drives are often too fast for the network interface.”

7. Use multiple layers of protection, where appropriate.

“Depending on the business value, time sensitivity, and critically of the data involved we apply different backup methods,” says Dan Funchion, senior manager of IT Infrastructure/Operations for SunGard Availability Services in Wayne, Penn. who is responsible for backing up or replicating 30TB of data daily. “In many cases we will implement multiple solutions for the same data sets (for example, remote replication combined with tape backup).”

8. Store a copy of the recovery plan with the backup data. Particularly when there is a major disaster, those who normally handle backup/restoration may not be available. Storing a copy of the plan with the tapes allows someone else to take the necessary steps.

9. Test the restoration process before it is needed, and test it on the actual equipment that will be used. This is particularly critical when you are planning on using a disaster recovery site that contains different servers or a different network architecture. When talking about a multitiered service, it doesn’t do any good to restore only one part. Or, if the application is used to looking for a piece of code or a file on a particular server in order to complete an operation, what will happen if it’s on a different server? So test the entire system, not just whether the files restore properly.

10. Set up routine file restoration as a help desk function. It doesn’t take a high level of expertise to restore someone’s accidentally deleted Word file.

“It is important to push as much of the restoration function to the help desk so storage professionals can work on improving levels of service,” says Robert L. Stevenson, Managing Director, Storage, for TheInfoPro, Inc. in New York City. “That will give you more flexibility to handle growth and address areas where there are inadequate backups.”

This article was first published on chúng tôi

Don’t Make These Mistakes While Grouting

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The end is near at this point in the backsplash tiling process. We’ve prepared the walls and we’ve installed the tile with thinset, letting it dry really well.

Today, we can talk about grouting, plus you can learn how to fix it if you mess it up as I did! I make mistakes, so you don’t have to!

This post contains affiliate links. By purchasing an item through an affiliate link, I earn a small commission at no extra cost to you. 

Part 3: Grouting a Backsplash

Part 2: Installing tile with thinset

Supplies Needed

First, we’re going to get the area as clean as possible. I used a shop-vac to remove any loose, dried thinset pieces. This also showed me that some of the tile pieces did not adhere as well as I had thought. So I reapplied thinset to those pieces and let it dry for another day. Sad, but necessary.

With a nice clean surface, you’re ready for grouting your tile. If you mixed it yourself, you want the consistency of icing.

Use the rubber float to apply the grout, using a diagonal motion to shove it firmly into the cracks. I like the smaller float because by this time, my hand was claw-like and everything hurt. It also was easier to maneuver than the larger one, because backsplashes are not very large.

Use the float again to remove the excess grout on the surface, being careful not to remove it from the cracks. Using an “S” shape pattern works well to remove all of the excess grout. I’ve read that working on 10-minute increments is a good rule. ***

Remove more grout than this!

After applying grout for 10 minutes, stop and grab the sponge and fill a bucket with water. It helps to have more than one. I used empty buckets that we had in the garage. You can buy empty buckets as well. They come in handy all the time!

Wring the sponge out so that it’s not sopping wet and start wiping the tile down, rinsing it in the bucket as necessary. You’ll have to rinse it a lot! Use the grout scrubber on any stubborn spots. Smooth the grout lines as you go, being careful to not remove too much grout. It should be fairly firm at this point.

When the water is gross, switch to a new bucket. Pour the old water outside. You don’t want it in your drains.

A little bit of leftover haze is normal and can be taken care of easily.

Continue until the grouting is done. Don’t rush this part. I’ll tell you why in a moment. Trust me. Use the 10 minute rule!

When you’re done, wipe off the layer of haze with a microfiber cloth.

***What I did wrong while grouting***

The aforementioned claw hands were part of the problem, but I was also tired of not having a kitchen. Ironically, if I had done it correctly, I would have had my kitchen back the next day.

I grouted the whole thing, and then went back to wipe it. My grout package said to let it dry for 30 minutes, but it was a really warm day, so I think it dried much faster.

I also did not wipe enough of the excess grout off in the initial grouting stage. Womp womp womp….

So it dried and was difficult to remove. But not impossible.

How to Fix Dried on Grout

Supplies Needed

Finishing up

Supplies:

Caulk

Caulk gun

Grout sealer

Caulk where the edges meet the countertop and anywhere else necessary, like along the windows or cabinets. I used white to match the white grout. If you mess up, you can let it dry and then scrape it off.

Let caulk dry.

Apply grout sealer. This part was really easy. I wiped a generous amount on, using the squeeze bottle to make sure that I got it really well behind the sink and stove where I make the most messes. Let it sit for a few minutes and wipe off the excess with a clean rag.

Still so much to do, but the tile sure looks lovely!

It still needs a few pieces of wood trim to be complete. I decided to add wood trim in my “problem areas.” I’m a big believer in not making work harder than it needs to be. It might not be “right”, but I would rather it be done and “good enough” than be curled up somewhere in fetal position crying. My method is not for perfectionists, because I’m not one. I’m a “get stuff done” kind of girl.

Anyways, instead of agonizing over cutting tile into perfect 1/4″ pieces, I decided to beef up the trim around my window instead. It’s a win-win situation because the trim is pretty wimpy.

Edited to add: I ended up adding thinner tile to the edges around the window. See the finished kitchen here.

As hard as this project ended up being for me, I still think of tile fondly. It’s like having a baby. It sucks while you’re doing it, but eventually you want another. (Except I would much rather have tile than more babies.)

Updated: I’ve repainted my cabinets and gave the kitchen a budget friendly makeover.

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Emy is a vintage obsessed mama of 2 DIYer who loves sharing affordable solutions for common home problems. You don’t need a giant budget to create a lovely home. Read more…

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