What is a KPI?

KPI or key performance indicators are values that you can accurately measure to show progress. It can be used for a business or personal life, or it can be used in terms of marketing. These are essential values that you can measure and can look at those values over time to know if your progress is advancing or decreasing.

Why set KPIs?

By setting KPIs you can make sure that you actually achieve your business goals and also that will tell you if you won’t. So you can go back to your strategy and you can tweak it and try again. They can be anything that is specific, measurable, and relevant to your business goals.

For example,

• Conversion rate.

By improving your conversion rate at each step of your customer journey you can get more customers.

• Relevant audience growth

Once you have worked out all your conversion rates, you may discover that your Instagram followers are more likely to buy. So growing your Instagram following could be a KPI.

• Email subscribers

If you find that your emails are sending you more customers, then one of your KPIs could be growing your email subscribers. When you set KPIs for each phase of your digital marketing and measure it regularly, you will be able to see what’s working and you will be able to go in and adjust your marketing as you go.

Where do you start with KPIs?

Start with your goal and work backwards through the funnel.

1. Awareness – It helps you to broaden your audience, so you can use things like organic social, advertising, influencer marketing, and large content projects, to help you reach new people. To set a KPI for this, you are looking to grow your audiences on the specific networks and channels that drive the most sales. Start by defining the channels, that are driving the most sales, then devise a plan that is going to help you increase your audience on those channels, and measure the relevant audience growth over time.

2. Consideration – is the phase, where people are a little bit further through the customer journey and they’re thinking about buying from you. To move more people onto the next phase, you need to reassure them that they are making the right decision. So content like testimonials and case studies, user-generated content, blog posts, and videos that answer every question that your customer may have is what works here. The more of this type of content your customers consume the more likely they are to buy.

What KPIs should we set for this?

• You can look at the number of pages viewed by each visitor to your website.
• Look at views on key content that is designed to convert.
• The time that people spent on your website.
• Link clicks to sales content from your social media channels and your emails.
• The number of email subscribers you have.
• The number of enquiry forms that are filled in.
• The number of people that are adding your product to the cart.

3. Sell– This is the ultimate goal. The obvious KPI for base is sales. But there are other metrics we can measure to see how successful our sales process is. This is where the conversion rate comes into its own. For your KPIs, you want to look at the conversion rate for each phase of the buying process. So from a website visitor to a landing page view, from a landing page view to somebody filling in an enquiry form, from an enquiry form to you setting up a sales call, from there to making the sales.

Set the right KPIs for your campaign – Tips

• Choose KPIs that are appropriate for the campaign’s position in the sales funnel. A direct response agency means that they’re not interested in things like clicks and impressions. When they can, they want to get down to sales and revenue. When a campaign’s primary goal is awareness or reach, they will look at things like impressions clicks, post-per-click, click-through-rate, and even video completions to tell how well or campaign is resonating with the target audience.
• Be aware of the limitations in your data structure.

The level agency uses the client’s system of record whenever possible for setting KPIs. This is great when the client’s system of record works as it should. When the CRM and marketing automation platforms and the advertising platforms themselves, all talk to each other and pass information between one another, that’s not always the case. If your systems aren’t talking to each other, if we are not passing UTM parameters or other advertising identifiers from the advertising into the sales platform or CRM, we can’t use those metrics as KPIs. That is why it is so important to set up your tracking. If you are not storing information from your advertising campaigns in your CRM, in your sales platform, or your other advertising system of record, you should be.

• Choose KPIs that operate on a reasonable time scale. Even if your campaign golds are tied to revenue or other direct sales KPIs, if you have a long sales cycle, it can be really hard to use those Metrics to optimize an advertising campaign. You have to go up the funnel to find the directional KPI that will tell us what the sales will be like in the future.
• Evaluate and optimize.

Once you have established good KPIs and benchmarks or targets that tell you how you are doing against each of those KPIs, it is time to set up a regular reporting schedule. KPIs are only good if they are useful. This means that you need to track your progress against them, and the actions that are coming out of those meetings consistently.

Customer Data : How do you use the most of it?

When you have more data than you know what to do with, finding effective ways to use the data can be difficult. 

 For example, with more  people using desktop computers, laptops and mobile  devices, all of which are generating more data, it makes sense that 90% of the world’s data has been created  in the last three years alone. And not just because people create data; this is due to algorithms and other programs that track user behavior and create their own data from it. 

 In fact,  daily  global computer usage currently generates more than 2.5 quintillion bytes of data, and this number is only growing due to the proliferation of IoT devices. This is a huge, almost incomprehensible amount of information. And only some of them are useful for specific relevant business interests. 

So how can a company sift through the mountain of data it collects every day and find the information that is really useful for improving performance, profits, sales or other operational factors? 

These 5 ways are some of the things a company can do to sift through  information and find what is meaningful and  useful. 

1. Accept that Big Data is here to stay.

Big data can look like a huge and unwieldy jumble of random information when viewed in an unpolished way. And  in that context, the real temptation is to  ignore it. However, to ignore big data is to ignore a major opportunity. For example, data science is a growing discipline because of the value that comes from the ability to sift, filter and interpret what is useful in big data. 

People who choose to ignore big data because of its volume are putting their business at risk. The first step to obtaining valuable customer data is to recognize that good data exists and be prepared to mine  it. 

 2. Invest in Analytics

The key  to getting the most out of big data, once you recognize its potential, is having the right tools and talents to wade into the ocean of data and find the most useful data. . . sense to you 

You should seriously consider allocating some operating budget to analytics. Larger companies may have entire departments dedicated to this work, but while this scale yields results, it is not the only way to obtain useful analysis. Even small and medium-sized businesses can find an analytics solution that fits their size and budget requirements, whether it’s staffing or software.

3. Use Historical Data

People often think of data as a way to  predict the future, but some of the most important lessons  data can teach us  come from the past. A good long-term plan for using customer data is to analyze historical data. 

Businesses should always be aware that  the best available data is a set collected over time. For example, you should not ignore sales data from the last 5-10 years, even if it is not part of your current digital infrastructure. 

Use document management systems and archive this data if necessary, but analysis tasked with obtaining past customer sales data can reveal incredibly useful information about customer behavior and buying habits. If you have existing data, even if it’s not digital, digitize it and make sure your software can access it. Under the right circumstances, it can be much more useful than you think.  

Of course, getting information about customer behavior and other data sets can  help  increase sales, but don’t forget that another way to make more money is to spend less. In addition to increasing sales, the right kind of customer data can also help  increase efficiency and reduce waste,  which can increase your bottom line. 

For example, your customer data shows that more and more of your marketing responses are coming from YouTube and Instagram, and less  from Facebook. This may indicate that for your product and target market, you can spend less or reduce your Facebook spend altogether and focus more on platforms that perform well. Let customer behavior data simplify your business.

4. Analyzing Customer Loss

“Customer loss” is a term used to describe the turnover  of customers or clients from  regular buyers to doing business elsewhere. This is another area where big data combined with analytics can make a big difference. 

 The purpose of this process is to review your user data and draw conclusions that help explain why some customers remain loyal and others support your business for a  period of time and then leave. You may find correlations between declining customer retention and the discontinuation of certain products. Alternatively, you may find that certain sales or seasons bring you a large increase in customers, but they don’t stick around afterward. By focusing on the specifics of customer attrition, 

 Analytics helps you understand how you can retain more customers and thus generate more consistent profits.

5. Social media is too much data

Up to 80% of the information produced today consists of videos, documents and images, a large part of which is published on social media. Analyzing social media and using the unfiltered, unsorted data it reveals can be extremely useful in not only identifying your niche, but also  what the market wants or is looking for. 

 It is important to understand that the content that appears on social networks can be a symptomatic indicator of other trends and factors that benefit companies that are turning around. So don’t think of social media as a channel to reach  your market, but realize that it can also be a window into what that market might be looking for, and you can get ahead of the market to give it to them. Don’t ignore trends, take advantage of them. 

Conclusion

More data is generated every day than any human or group of humans can reasonably track. Beneath that data, however, is a wealth of useful and actionable insights. Businesses can only increase sales through strategy and sensitivity when selecting, analyzing, and using the right data correctly.

Tech that will enhance your brand’s customer experience

In the digital world, exciting new technologies such as virtual reality, cloud computing, big data, real-time video connections and “smart” chatbots are redefining how companies interact with their customers. 

Staying on top of these developments and trends requires mastering these new innovations and using them in innovative ways to communicate, engage and promote. Organizations willing to embrace the creativity that technology offers and go beyond the “norm” will differentiate themselves from the competition and offer new and richer customer experiences to their customers. 

 This article examines five of the most talked about technologies of the moment, providing insight into their potential to deliver the best possible customer experience. 

1) VR: Engage and Immerse

Perhaps more than any other technology today, virtual reality has the potential to fundamentally change the way we define  customer experience. 

 Customer Experience VR, used by many brands, can engage consumers by providing them with new  product or service experiences. Designed to provide a sensory experience, it captures the consumer’s attention and imagination like no other technology, and visionary marketers  are making the most of its uniqueness. Image of 

 Guinness VR booth  

  Guinness has developed a new VR tasting booth for consumers in Tesco stores in the UK that stimulates all five senses. To present the new beers –  West Indies Porter, Hop House 13 Lager and Guinness Draft – the brand used the expertise of Guinness Brewer Peter Simpson to narrate an immersive 360-degree video, while a food and taste scientist from the University of Oxford. Colors, textures, movements and sounds were used to ensure they matched the taste of each beer. 

 “We have never stopped innovating  beer, taste and technology. VR is an immersive way to bring our beer flavor profiles  to life. We hope that buyers will appreciate Guinness beer in a new light – and maybe, as a beer, they might not have thought to try anything else. – Halie Ritterman, Global Head of Digital and Data, Guinness.

2) Artificial Intelligence: Communicate and Learn

Although since the 50s, brands have  started to effectively use AI  for core consumer services. The ever-evolving AI has tremendous potential to help improve customer self-service, improve personalization, and respond to individual customer wants and needs in  unique ways. 

 For example, the Hilton hotel chain. The brand wanted to make artificial intelligence part of its customer experience and partnered with IBM to create the industry’s first robotic restaurant concierge service Watson to answer customer questions. Using cognitive reasoning and robotics, the bot provides  unique interactions with consumers, and the more it interacts, the more it learns  to provide assistance. 

 While creating a robot may seem like an extreme example of  technology, it shows the potential of artificial intelligence to deliver an unparalleled customer experience. A technology that should not  be ignored, it has the potential to communicate and learn, making it a useful technology to improve the customer experience.

3) Chatbots: Improve Responses

Whether or not you believe the Microsoft CEO  that “bots are the new software”, the fact is that these particular tools are turning heads. Today’s industry-standard chat, with algorithmic learning that allows it to learn from past conversations and adapt responses, is a great step forward for brands that want to turn simple, routine questions and meetings into an intelligent system. 

 Adidas Studio LDN Chatbot 

 Let’s take Adidas as an example of a brand that has figured out how to use this new technology. Using Facebook Messenger and a specially designed AI bot, Adidas was able to increase consumer awareness  and engagement with its new community space, Studio LDN. Designed to drive brand engagement, the studio offers free weekly training sessions for women that can only be booked through the chat. 

Using this bot helped reduce the time and effort required to sign up for  Studio. Realizing that their target market lives fast and busy lives, Adidas has developed a powerful intermediary to ensure optimal conversion. 

The campaign resulted in nearly 2,000 people signing up for Studio LDN within the first two weeks, with 80% repeat usage. Adidas believes that 60 percent weekly consumer retention has helped the bot-based booking system speed up an otherwise tedious process and significantly improve its bottom line.

4) Internet of Things (IoT): Multiple Connections

According to studies, businesses are the biggest adopters of IoT solutions due to the benefits it offers. It can improve a company’s bottom line by reducing operating costs, increasing productivity and helping brands expand into new markets or develop new products. 

Furthermore, the extent to which  IoT enables synergy and connectivity between platforms has catalyzed the growth of new types of products. Brands can now use this technology to foster direct connections between physical activities and digital interactions to execute advertising campaigns across platforms. It also enables an engaging story that allows customers to interact with your product or  service. 

 Products like the FitBit are a perfect example of real hardware that provides users with valuable social capital. Because it’s essentially integrated into the Internet, it’s easy for customers to upload their workout results to platforms like Facebook, which in turn inspires new audiences to buy their own FitBit.

 Fitness groups, personal training programs and hobby clubs have all been developed across Facebook, using FitBit to track progress and share data. Simply put, FitBit’s embrace of the Internet of Things ushered in a new fitness paradigm online.

5) Programmatic Advertising: Superior Targeting

With  programmatic spending, growing brands are investing in using data to ensure the right ad reaches the right person at the right time.  The key to programming is that it uses technology and the resulting analytics to help brands understand as much as possible.

It can feel like we are always on high alert in the world of digital media, particularly in paid search, waiting for the next product announcement or new beta that will help us squeeze incremental performance out of our paid marketing budget.

Therefore, it may seem counterintuitive that the product that has been around since Google AdWords’ inception, more than two decades ago, will be the single most significant addition to your paid search program in 2022. That product is Broad Match.

What is the prize’s value?

Google’s internal research indicates that advertisers using broad match and smart bidding experience a 30% average conversion increase at a similar CPA. If your KPI is conversion value rather than conversions, for instance, the exact figure you hear will not deviate too much from this 30% mark, although the exact nature of the test may influence the quoted figure.

In order to provide our clients with the most effective solutions, it is our responsibility as an agency to carry out our own experiments that either confirm or disprove the claims made by our media partners. We have made significant investments in this capability at Brainlabs, and our “Hippocampus” database enables us to track the outcomes of all agency-wide tests.

Two significant findings emerged from our extensive recent testing of Broad Match.

1. Google’s claims were supported by convincing evidence that we discovered. The median uplift we observed was +19%, which is not a figure to be laughed at even though it was just below the 30% mark.

2. Perhaps even more intriguingly, our analysis demonstrated how much can be concealed behind an average. Not only did we observe a remarkable median uplift, but we also observed that broad match consistently delivered successful tests. Broad match emerged as the winning variant on 46 of the 54 tests we have documented. A success rate of 85 percent is almost unheard of in digital media testing given the wide range of external factors that can influence it.

But let’s step away from the finer points for a moment. You can’t afford to ignore that number, regardless of whether the increase is 19 percent or 30 percent, especially for a feature whose implementation requires almost no effort. The good news is that your budget doesn’t have to stretch as far as a 19% increase: Instead, you can use that added value to improve your CPA or ROAS goals by enabling broad match and maintaining your current investment.

Broad match is the only solution to paid advertising’s problems.

How did we arrive here?

It’s not hard to understand why broad match has earned a bad reputation over the years. In the past, the presence of a broad match in an account was a sure sign of a hands-off management style, which resulted in subpar results and ads served to users who were not even close to buying your product.

The rise of the broad match has been the story of steady and gradual technological advancement over time. Even though there is a lot of talk about it now, few people outside of Google’s engineering and leadership teams probably could have predicted how big a hit it would be more than three years ago.

In February 2021, there was a turning point if ever there was one. Google informed the industry in one of its most important announcements of the year:

The fact that the algorithm had fundamentally shifted away from syntactic matching to semantic matching was encapsulated in that small print. As a result of this change, broad match stopped being a firehose and became a really useful tool for accurately expanding your ad targeting.
The item upgrades haven’t halted there, and today, Google’s vision for wide match keeps on mirroring a gradual process of updates and execution improvements:

Using cutting-edge natural language recognition algorithms, continuously improving data quality and infrastructure, simplifying broad match management, updating the keyword prioritization process, and establishing a joint optimization process for creative, bidding, and keyword targeting. Of course, Google’s current approach to discussing broad matches with advertisers and agencies is anything but subtle.

One of the opportunities that consistently rank highly is the “upgrade your existing keywords to broad match” call to action, which can be found in the recommendations tab of Google accounts all over the world.

The steady stream of product modifications and enhancements will continue despite Google’s bolder communication strategy, with the possibility that many of them will go unnoticed for the most part.

When Is a Broad Match a Bad Match?

In paid search, auction-time bidding is table stakes, as you probably already know. However, this is especially true when the broad match is used. If you aren’t tailoring your bids in real-time with this Google Ads feature, a broad match will almost certainly result in you spending a lot of money on a lot of users who have very little interest in your product at the moment.

However, in the opposite direction of that logic, it is essential to recognize the value that some of those queries that appear to be more fragile bring to the table when combined with smart bidding. We can easily read a search query report, find a few questionable examples, and overreact as humans: We must exclude these queries because they will almost never convert for us!

However, as long as those users have a probability of conversion that is not zero, you are justified in serving an advertisement by setting an appropriate low bid. To be clear, we are not advocating completely hands-off handling of search query reports; you will still need to employ some human judgment. However, if you’re after performance, you should try to give the algorithm as much freedom to optimize as you can handle.

Focusing on the wrong metrics is another common error. After implementing broad match, your paid search account’s dynamics will change, but that’s okay because the numbers you care about will be moving in the right direction. If everything else is equal, switching to a broad match should typically result in the following changes to your campaign metrics:

It is true that some of these numbers are negative, and the less confident marketers in the room are already asking, “Why are my CTR and conversion rate going down?!?”It must be driving less qualified traffic through the broad match!”But the point is that you’ve added value and increased conversions with that additional traffic, and your CPA and ROAS haven’t changed because your bid strategy has paid less for clicks.

Lastly, being able to direct Google’s automation in the right direction is becoming increasingly important. Remember: An algorithm will optimize solely with the intention of achieving a conversion objective. Therefore, you should be prepared to see an increase in low-quality customers if you haven’t developed a conversion goal that is sophisticated enough to distinguish between your most valuable and least valuable customers.

That could mean MQLs that never turn into sales or one-time customers who never return for more purchases, depending on your business. This trade-off can be mitigated by sharing first-party conversion data with Google.

Conclusion

You have every right to be skeptical of broad matches as a mature, world-weary PPC marketer. Make an effort to overcome that, and keep in mind the steady advancements in machine learning.

Keep your attention on the goals of your marketing while you undergo that mental shift, and ideally, consider ways to advance these goals to better target your most valuable customers.
However, the most important thing is to act immediately—do not let the 19% increase pass you by. It would not be an exaggeration to say that broad match has reached the point where we would consider it an essential component of your search strategy. If it isn’t on your list, figure out how to bring it to the forefront and start testing right away.