Tag: analytics

3 Keys To Optimizing Customer Performance Analytics

Post author By Jon Rognerud
Post date August 6, 2018

If you’re not leveraging customer analytics, you may be selling your business short.

In fact, companies that subscribe to the practice of collecting and leveraging customer analytics significantly outperform their competitors, according to McKinsey.

Moreover, firms that make extensive use of customer analytics are more than twice as likely as their competitors to generate above-average profit, sales and ROI — and they’re nearly three times as likely to generate superior revenue growth.

Achieving these types of results requires employing a smart customer analytics strategy.

In other words, merely having your IT department gather data without a solid strategy in place won’t automatically translate into financial improvements.

With that in mind, here are three keys to effectively leverage your customer analytics data for optimal business performance.

1. Draw Data from All Channels

In order to leverage customer analytics successfully, you need to base your analysis on a comprehensive view of data throughout your organization.

Sure, companies that work with data in silos may collect plenty of pertinent information, but they’re capturing just a snapshot of the buyers’ cycle, thereby only seeing a distorted view of their customers.

These days, customers expect the brands with which they do business to offer a comprehensive and efficient omni-channel experience.

In particular, implementing an omni-channel data-collection strategy should span all customer-facing departments of your company.

This includes marketing, sales and customer service.

Additionally, data collection should encompass all channels your customers use to interact with these departments.

For instance, your marketing data may include information collected from social media, mobile text messaging, email and other channels.

2. Integrate Your Analysis

Collecting data across all channels is only a preliminary step.

In order to put data to practical use, customer information assembled from various support channels should be collected into a central database for coordinated analysis.

This poses the challenge of how to synthesize data from multiple channels into a coherent whole. Ultimately, your company’s ability to integrate data effectively is heavily impacted by your software selection.

Software platforms that are designed to combine and analyze data from multiple sources greatly increase the efficiency of data integration.

For example, using an automation platform that tracks your online marketing practices across multiple channels makes it easier to obtain a holistic view of your various internet marketing campaigns, rather than having to log into each channel separately to perform an individual analysis.

Moreover, using a cloud-based call contact center allows you to pool your customer service data from all support channels, including chatbots, social media, mobile apps and interactive voice response.

3. Use KPIs and Benchmarks to Track Performance

In order to translate your data analysis into actionable outcomes, it’s vital to prioritize which key performance indicators to track and to set benchmarks that measure performance.

One of the most important KPIs to track is customer satisfaction scores.

In particular, soliciting feedback through post-sales surveys is one popular way to measure satisfaction.

Additionally, providing a means and encouraging your customers to interact with your brand on Facebook and Twitter is another cost-efficient way to gather data on satisfaction levels.

Other important customer-centric KPIs to track include customer lifetime value, customer acquisition costs, customer engagement and customer churn rates.

Additionally, it’s important to segment the performance of individual marketing channels and sales campaigns, allowing you to see how well your marketing and sales efforts are working.

However, you can improve the performance of your marketing and sales efforts by doing segmented tracking of the different customer demographics you serve so that you can see how well customers are responding to different promotions and offers.

You can then do split-testing for different demographic groups to adjust and improve your marketing and sales performance.

Smart use of customer analytics strategies can give your business a big boost.

Firstly, taking an omni-channel approach to data collection provides you with a complete picture of your customer interactions.

Then, through the use of integrated software tools, you’re able to better analyze your data and improve the ease and efficiency of your analysis.

Finally, employing KPIs and various other benchmarks enable you to translate your analytic-collecting efforts into practical, profitable results.

Understanding data is essential, and everything starts with a performance audit.

Tags analytics

Big Data General

How Your Existing Customer Data Can Help You Predict the Future

Post author By Jon Rognerud
Post date March 26, 2015

CRM data to drive traffic via targeting measurement and personalization

Your existing CRM data is a treasure trove. But, you are likely not using it properly. Certainly not in today’s new ways of extracting and positioning that data for online use in your marketing. You are missing a huge opportunity. You can use that data (that you already own) to drive more targeted business using your existing customer data. Learn more about your own data, use it wisely in your marketing, and you can begin to predict the future for potential traffic, sales and bottom line profits.

Gone are the days when print marketing was used to reach existing and potential customers. Today’s marketing professionals understand how using CRM data to synchronize sales and marketing efforts, across various digital mediums, is an imperative part of an effective business plan.

A positive, return-of-investment ad campaign is only deemed so when the click-though and purchase rates are satisfactory enough to justify the time, effort and financial costs associated with them.

This is where the union between measurement, targeting and personalization all come into play.

Measurement

Setting pre-defined goals for each campaign allows marketers to determine whether a campaign was a success.

Whether it is through the use of A/B testing, a percentage of views/clicks/submissions or through the use of some other metrics, the goal is to target an audience and have them end up, not as a customer in the monthly/quarterly/yearly sales cycle, but as a life-long business relationship.

Regardless of which type of advertising medium, or combination thereof, a business will choose; the goal of all effective advertising campaigns is to reach a customer, despite where they are (online, off-line, mobile). An effective marketer can only measure customers he or she has reached.

What about the others that slipped away?

Targeting

Look-alike modeling, also known as a Lookalike Audience, is currently a marketing practice used by social media giant Facebook. A Lookalike Audience is a group of prospects targeted based on the customer personas a particular business wishes to reach.

In addition to gaining new followers for your business and boosting your brand’s social media presence, these prospective custom audiences are also an asset when vying for additional landing page sell-through revenues. Other online big data service marketing providers like Liveramp – provides lookalike audiences for CRM.

Targeted groups can be reached during various points of the customer lifecycle stage and look-alike modeling can be used, not only as an inexpensive way to gain new prospects but to test the effectiveness of new calls-to-action.

With metrics factored in, a business can have measurable results based on existing customer bases while capturing new, Lookalike Audiences and evaluating their response rates.

Personalization

To ensure both active and potential customers receive personalized service, multi-channel marketing can be implemented throughout the use of social media outlets. Interactive digital campaigns should be used to deliver online ads to an intended group of consumers previously served by email or direct mail.

When these personalized marketing campaigns are cohesively aligned with CRM programs, actionable results can include:

Cost savings from having to pay for direct mail-related expenses and the avoidance of mail not reaching the intended recipient.
Reduction of emails being sent to spam folders; thus never being read.
Client reporting becomes easier as each specific campaign’s overall performance metrics are actionably measured, reported and archived for future use.
Ability to increase a business’ social media presence through the use of instant social media postings, landing page redirects, video marketing and other new-media.

Can Traditional and Digital Media Be Used Together In the CRM Experience?

The answer is certainly yes; if it will help increase your business’ overall bottom line and provide superior customer service. Again, this is where understanding your targeted customer demographic and personas come into play.

When implementing the true form of multi-channel marketing, customer interaction and acquisition are the goals. This means customer engagement and response could come from a direct mail catalog, visiting a business’ retail location, reading updates on a social media site, or instantly connecting with a mobile application.

Since an audience will need to be receptive to campaigns, A/B testing was mentioned earlier, but don’t forget about frequent digital content updates and making them relevant. Remember, the first 160 characters in any message are the most important, especially those delivered on mobile devices.

Attention-grabbing headlines, promotions and calls-to-action are a priority, and when executed effectively, can help increase a business’ CRM database, overall service reputation, attainable digital audience, and prospective yearly revenue.

To learn more about utilizing your existing customer data, and how you can leverage it for driving traffic and real customer engagements – get more information here.

Tags analytics, big data, crm, pixeling, sales

Analytics

Big Data Analytics And Social Media – The Hype And The Promise

Post author By Jon Rognerud
Post date August 4, 2013

Big Data and What You Can Do With It

The amount of data in our world has been exploding. Eric Schmidt at Google has stated: “Every 2 Days We Create As Much Information As We Did Up To 2003“. (Techcrunch).

Imagine the scope! And, analyzing large data sets, called Big Data, is becoming a large basis of use for businesses and their competitors alike. “Data” is important to every aspect of business. However, data is especially powerful to those seeking to leverage search, social, mobile, local, video, marketing and emerging technologies to compete, provide actionable intelligence to executive teams, provide better customer experiences and earn more market share.

Big Data is a term often associated with Fortune 500 and 1000 companies because these enterprises often have greater resources to invest into the collection and analysis of data. If you’re a social media “expert” and you don’t know the connection between Big Data and Social Media, then you should sit up and take notice.

Social Media by the Numbers – Twitter/Facebook

The popularity of social networking has dramatically increased in recent years. Today, there are more than 1.11 billion Facebook users and 500 million Twitter accounts. This growth has led to a rise in the amount of data created daily, with Facebook reporting 665 million active users each day. Moreover, with the increased interest in Big Data and the capabilities it provides, everyone is suddenly interested to discover exactly what it can do for their business.

With the growing prevalence of users to post an abundance of information about their everyday lives, it provides businesses an opportunity to monitor the data and identify patterns of behavior in individual users. However, due to the vast amount of data produced by social networks on a daily basis, the analysis of this information cannot be performed with a mere software algorithm; rather it must be done using Big Data analytics.

What is Big Data?

Big Data is a collection of both structured and unstructured data sets that are so immense, ranging from a few dozen terabytes to several petabytes. The data is beyond the ability of regular software tools to capture, manage, and process it within a reasonable period of time. Unstructured data, which constitutes around 90 percent of Big Data, is made up of emails, social media posts, tweets, videos, mobile phone calls, and website clicks. The Interwebs provides gargantuan user-generated content (UGC). Structured data makes up the remainder of Big Data and is information contained in databases.

Big Data Analytics is where businesses derive new meaning from new data sources. New, meaning that was never practical to discover before. This could be because of scale, data formats, the distribution of data in many locations, or the fact that no one thought of looking before – or how to make use of it in the first place. It is easily as much a new mindset as it is new technology. Executives and technologists are continuing the discussion, but real world applications are now put to use. Tableau Software provides analytics in the cloud right now.

Who are the Largest Players in Big Data?

A science team at a leading edge technology firm that leverages massive Twitter historical data and many other social media datastreams – @datasift – analyzed the social interaction around big data in 2012. The result was shown in the big data social media infographic. The top five big data related tweets were Apache, 10gen, IBM, HP and Teradata. And, when it comes to big data services and infrastructures, don’t miss The Big Data 100.

Why Should Businesses Care?

Businesses must care about Big Data so they can learn what to offer, to whom, when to offer something new, and what channels to use. It can also help them know if they can handle problems themselves or they need to get outside help, which competitor might be winning. Shareholders and upward moving company stock prices will reflect victories in this area. Big Data will be the one of the most important things for business since the Internet due to the business insights that it can provide. However, a small mom-and-pop business may not use at this massive scale, but can get social media analytics and reports from tools like Hootsuite today.

Big Data and Social Analytics

Historically, data analytics software hasn’t had the capability to take a large data set and use it to compile a complete analysis for a query. Instead, it has relied on representative samplings or subsets of the information to render results. That approach is changing with the emergence of new Big Data analytics engines, such as the opensource Apache Hadoop.

Hadoop processes large caches of data by breaking them into smaller, more accessible batches and distributing them to multiple servers to analyze. Hadoop then processes queries and delivers the requested results in far quicker than old‐school analytics software—most often minutes instead of hours or days. Hadoop and other such systems provide complete looks at big data sets, instead of a team of analysts spending days or weeks preparing the parameters for data subsets and percent samplings.

Generate and Analyze

So with this overload of data, you must understand how it can be analyzed. Keep in mind the difference between just “data” and the “right data” – data that drives actions. With social media, it can be confusing as to which data is “right,” but again, focus on data that drives actions – either a change in business processes or a change in behaviors. The key to fostering the growth of social media and Big Data is understanding how to make each work individually – one to generate the “right data,” and the other to process and analyze the data.

By using specific social media monitoring platforms such as Radian6 and Buddy Media, you are half way there and can take this data and use the specific results to drive campaigns. You can appeal to the masses by tracking trends, addressing consumer concerns through their feedback, and identifying key influencers who can become brand advocates. These are all excellent ways of using the power of big social media data analysis. Big data analytics platforms like Paraccel may be considered for larger enterprises.

Experience the Power of Data

If you’re actively working on any digital aspect of a brand without the benefit of data, you’re just wasting your time. In this digital age, it is essential to identify trends and opportunities. Now, more than ever, data will play a vital role in every aspect of business. Data always has been a goldmine for marketers (strategy, social, search, SEO, PPC, PR).

However, it’s safe to say that the anticipated growth of data and emerging use of unstructured data are game-changers. Working with Big Data and Social Media will only lead to greater success as technology continues to advance. Those who recognize and embrace the power of this mountain of data early on are most likely reap the most rewards.

You can learn more about digital analytics and big data from our analytics primer.

Tags analytics, big data, Social Media