Marketing Data Strategy

Marketing Data Strategy: 5 Business Downfalls in 2019

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In 2019, businesses need to have a data strategy to not be left behind

Downfalls of not having a marketing data strategy

As funnel data consultants, we speak with executives and business owners across many different industries. The common link between all of these organizations is that they know that they need a data strategy in order to stay competitive in their industry. Every company; no matter if they are small, medium or large needs a marketing data strategy. Without taking advantage of their data, their growth is stagnating. They are realizing that not having a funnel data strategy is costing them business, and they are aggressively trying to catch up.

The modern world of digital marketing has sophisticated lead management and customer management platforms, visitor tracking, user behavior monitoring and other emerging technologies. As a result, these systems are generating a huge amount of data. Your business must have a marketing data strategy that identifies how this data can be used to your benefit. Examples include optimizing marketing spend, converting more leads to customers and generating higher customer lifetime value.

1. Funnel Data is not Accessible

Businesses continue to spread their operations over more and more systems as cloud applications take over. Businesses are choosing a best of breed approach with their technology. They are choosing specific applications and platforms based on features over a consolidated platform approach. Consequently, seeing the full picture will be difficult since your data is being created in silos.

Some try to solve this by pulling data from each system and combining it manually in spreadsheets. This approach is very labor intensive, error prone and typically does not allow for multiple data refreshes in the same day. Others try to pick one system to push data into from all other systems, but in most cases this is a square peg in a round hole. This is because the data needs to retain its structure and scope in order to remain complete and accurate. In order to maximize the value of the data it needs to be consolidated in a common location which is accessible by the reporting tools for additional analysis and transformations based on business needs.

2. Key marketing metrics and funnel steps are not measured

If you could easily choose, would you rather generate 100 leads which cost $2,000 or 70 leads which cost $2,100? The cost per lead would be $20 and $30 respectively. For example, if you were optimizing around lead volume and overall cost per lead, you would likely choose the first. Now, what if you were able to see that the leads from the first source converted at 5% and had a lifetime value of $800, putting your total revenue at $4,000. The leads from the second source converted at 10% and had a lifetime value of $1,100, putting your total revenue at $7,700. The $2,000 marketing investment would create $2,000 in margin where the $2,100 marketing investment would create $5,600 in margin. Knowing that would probably give you more confidence that the second strategy would be more beneficial for your business. The reality is that most businesses do not have full funnel visibility and these metrics are simply not able to be measured. Getting to this level of detail requires a mature marketing data strategy and associated business processes which accurately capture the required data points.

Beyond marketing performance analysis, there is also huge potential in the sales process for performance analysis. The sales process data can be invaluable to evaluate team and individual sales representative performance. For instance, the metrics that are below average will put a spotlight on problems or training issues so that your sales teams can be efficient in solving the exact problems that are limiting your sales potential. Sales data should be tied back to marketing sources so that you can evaluate metrics like contact rate as another performance indicator. The critical sales metrics can also help you distinguish between marketing or sales performance issues to optimize growth investment strategies. Improving sales funnel performance also improves overall marketing cost per acquisition.

3. Attribution accuracy is not a priority

Marketing attribution often has significant gaps and is simply not made a priority of the organization. In addition, organizations don’t really know who is responsible for attribution accuracy. Is it IT, Marketing, or Agency partners?

In the midst of this chaos, organizations usually lump tactics together into broad categories, which does not allow for tactic level analysis and optimization. As an example, organizations may be able to evaluate paid search overall, but are unable to evaluate a specific non-branded paid search keyword tactic all the way through to revenue.

This issue exists because marketing attribution data is not being collected or is getting lost in the pipeline between prospects, data, and marketing reports. The data and its integrity must be in place to make fact-based growth decisions for your business. End-to-end attribution auditing of each marketing source from organic search, to search engine marketing to even billboard advertising should be done regularly. Any issues found causing inaccuracies should be viewed as a priority and fixed. Businesses should be able to attribute their entire click/visit to revenue funnel back to the source or sources that influenced that customer journey. In addition, it must be maintained as technologies change or new marketing sources are introduced.

4. First touch, last touch or multi-touch attribution models do not exist

The journeys that prospects make from the first engagement with your brand to the time they convert to a customer are getting longer. Each step of the journey is a marketing tactic being used by your business to capture the attention of the prospect. How will you know the value of each tactic and how it is contributing to your marketing strategy’s success?

Businesses with insights into their data are figuring out ways to optimize marketing in new ways. One of these ways is to analyze outcomes against different marketing attribution models. Digital marketing opens the door to multiple interactions with a prospective customer. Companies are aware of which initial marketing effort is tied to a customer conversion. However, this is no longer a valid tactic. Other factors need to be looked at throughout the entire customer journey to see what other marketing efforts influenced them. To do so, you must have fine grained data collection and business logic created to identify each attribution type. Once you have this, a deeper analysis can be conducted to view metrics based on any of the attribution model dimensions.

5. Lead data management practices are distorting the truth

How does your CRM handle duplicate prospect records? Do you have a set of automated merging rules? Are your leads merged manually in an unpredictable way? When you merge do you lose information about the old or new lead? What dictates if a lead is a true duplicate, a re-inquiry or a net new lead? When running reports on data, re all of these scenarios accounted for? Considering all of this, experience has shown that in many businesses these practices need work to ensure that marketing attribution is accurate.

Lead management systems and business processes will have to support the goal of providing the data that can be used for the previously described business intelligence. Preserving lead source attribution data has to be your mission. This will tie to the individual lead which was generated by that source. You need sound processes and procedures that will handle subsequent leads for the same individual to track that interaction and all related sourcing data. Consistent definitions should be developed to determine when a lead is a re-inquiry or a net new lead.

How do I create a marketing data strategy?

Creating a data strategy for marketing requires a multidisciplinary combination of knowledge. While they have numerous resources, large organizations struggle with creating data strategies when there are too many competing interests. Confirmation bias, politics, cultures and egos often prevent good data strategies from being conceived. Likewise, smaller organizations struggle because they simply do not have the resources to cover all of the required areas of expertise. Finding a good marketing data science partner will help solves these problems. Find a data science consultant that has expertise in marketing, digital advertising, sales processes, software platforms, data engineering and data analytics.

I have a data strategy, now what?

After creating your data strategy, it now needs to come to life. Software products are prevalent, however businesses rarely find success by using them. Instead, your business does not need a product, it needs a solution. A solution gives you precisely what you need to optimize marketing and sales. It ensures accuracy, at inception and into the future. The solution is agile, to adapt as your processes or technology platforms change. Choose a partner that excels at building marketing data solutions rather than selling a product or producing deliverables.

Contact us today to kick-start your marketing data strategy.


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