Written by the Institute in collaboration with

A supplement to Shopper Marketing magazine

Bridging Data's Digital Divide

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Where the Journey BeginsPercent of Purchases by Referring Site

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YoutubeYahooFacebookGmailDirect to Purchase Site

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Growing Reliance on On-Site SearchPercent of Sales Starting with Search

27% 60% 4% 10%

38% 45% 8% 10%

33% 55% 4% 9%

Cookies

Dry Dog Food

Whey Protein Powder

Non-Search On-site O�-site Both

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By filling critical gaps in their online datasets, marketers can gain deeper insights into how consumers shop across all channels and thus influence purchase behavior throughout the entire decision journey.

EXECUTIVE SUMMARYn Most consumer goods and retail marketers lack the full cross-channel, cross-

category view of the consumer necessary to capitalize on the accelerating digital shopping trend.

n There is a widely varying "maturity curve" across industries and sectors with regard to mastering the consumer decision journey, especially in the digital portion and post-purchase phase.

n Marketers can learn more about the interim purchase steps online than in a physi-cal store, thanks to online datasets; once they uncover patterns, they can develop strategies to communicate with shoppers in more targeted and influential ways.

n One useful approach for analyzing the consumer decision journey is to break it into four major stages: Discover; Consider; Evaluate; and Purchase.

n Right now, data in most CPG companies still resides in different business units and disparate systems, overseen by different functions within the marketing department. Success will hinge on the consolidation of this data.

Where the Journey BeginsPercent of Purchases by Referring Site

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or many marketers, predicting consumer behavior must seem more elusive than ever. Today’s consumer has a constantly expanding arsenal of tools and opportunities to shop whenever and wher-ever he or she wants. Factors such as unlimited access to product information through mobile devices and increasingly influential brand conversations in social media have created a base of shop-

pers whose interests and loyalties are constantly shifting. According to McK-insey’s research, well over half of consumers — 58% — switch brands from one purchase cycle to the next.

Today’s shopper journey is also growing more complex and difficult to predict. Even the most nimble of consumer goods companies cannot re-act quickly enough because the consumer is generating vast amounts of data throughout a decision journey that is disjointed and difficult to uni-fy. Thus, while most consumer goods and retail marketers recognize that e-commerce is critical to the future of their businesses, they often lack the full cross-channel, cross-category view of the consumer necessary to capitalize on the accelerating digital shopping trend. By 2022, e-commerce in the U.S. will ac-count for 10% of total consumer goods sales (most current estimates are now in the 3-5% range), according to research firm Statista.

Exactly why marketers have yet to ideally position themselves for the digi-tal future is a complicated issue. Part of the challenge comes from within the organization, as many companies have been slow to break down the silos be-tween brick-and-mortar and e-commerce operations. Even companies that have made major strides in this area and have the right tools and technologies in place agree that there are major gaps in the data that can, and must, be filled.

“Certainly the data landscape is working to fast adapt to this new environment, but there is still a lot of fragmentation, too many touch points and too much vari-ability in standardization of data capture methodology that limits the ability to

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Complex Digital Buying Environment: The consumer decision journey is an increasingly complex and circuitous path in which consumers are generating vast amounts of data that are disjointed and difficult to unify.

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conduct analytics at the same level and with the same ease as measuring offline performance,” says Elizabeth Slattery, Senior Manager of Data Assets and Methods at The Coca-Cola Company. “However, there is also the benefit of new technolo-gies and real-time metrics that previously weren’t available.”

EMBRACING THE MODERN CONSUMER DECISION JOURNEYIn recent years, brands and retailers have used a variety of predictive analytics tools in order to map the consumer decision journey with added layers of nu-ance and understanding. The results have produced unique insights into how consumers shop in various categories. In the pet food category, for example, consumers are increasingly being influenced by online sources of information such as third-party ratings and reviews from Amazon and independent blog-gers, regardless of how or where they buy the products, says Caty Grzymajlo, Senior Director of Insights and International Marketing at Nature’s Variety, which owns the natural and raw pet food brands Instinct and Prairie.

“We used to get consumer decision hierarchies for brick-and-mortar stores that might adjust a little bit depending on the particular retailer, but now there are so many paths involving digital channels that the journey can go in seem-ingly endless directions,” says Grzymajlo. “It’s amazing because it allows us to create a tailored, multi-channel experience based on how we’re targeting or re-targeting customers through media. But at the same time, it brings so much difficulty and complexity to everything we do.”

There is a maturity curve in different industries and sectors with regard to mastering the consumer decision journey, notes Andy Mantis, Senior Vice President of 1010reveal, 1010data’s consumer insights business. “For consumer goods companies, it often depends on the acumen of the individuals involved and whether their background is in market research and analytics, versus hav-ing a more strategic or insights background.”

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Key questions for marketers at major stages along the journey:

Discover: Is the choice of advertising channels optimized and truly effective? Are marketing messages aligned with current or future consumer trends?

Consider: Can consumers seamlessly find the products as they gather information? How are digital tools like keyword search influencing buying behaviors online?

Evaluate: Which other brands or retailers are consumers considering before purchasing? How are third-party reviews or opinion leaders impacting purchase decisions?

Purchase: Is the brand’s channel strategy diversified enough to meet consumers where they are?

As of today, the typical marketer’s understanding of the decision journey remains incomplete in a couple of key areas:

n The digital portion of the journey Most marketers have a thorough view of how their brands perform relative to the category in stores, thanks to retailer POS data and shopper panels from commonly available industry sources. However, such a comprehensive set of data is not as easily obtained for online shopping. Data from Amazon.com, for example, is typically confined to how individual brands and SKUs are performing on the site. And there are hundreds of other e-commerce sites that sell consumer products for which little to no information is available outside data collection from a third-party provider. Absent a direct-to-consumer channel or access to independent data sources, consumer brands have a much more lim-ited contextual understanding of their online perfor-mance versus at major U.S. retailers.

n The post-purchase phase While marketers have a solid grasp of the steps lead-ing to the in-store purchase, they are often not doing enough to uncover the “whys” behind customer expe-rience and satisfaction, or to tie up the loyalty loop by using post-purchase data like customer feedback and ratings and reviews. Understanding why customers are lost in one purchase cycle can help inform strategies to convert more buyers in the pre-purchase phases of the next cycle. These are critical insights, given that acquiring a new customer is anywhere from five to 25 times more costly than retaining an existing one, de-pending on the industry or survey. On the other hand, increasing customer retention rates by 5% can increase profits by anywhere from 25% to 95%, according to Bain and Company.

Marketers can fill in the missing data link as part of a more unified and com-prehensive approach to data collection and management. That often requires taking an inventory of all the data sets being used within the organization and determining the most cost-effective ways to close the gaps (for more on this topic, see “Valuing Data,” page 9).

Loyalty, meanwhile, is perhaps more fleeting than ever. Just 3% of consumers spent more than 50% of their wallet at one retailer across in-store and online chan-nels in 2017, per 1010data. Even though this is a small segment of consumers, it boasts an average basket of $274, which is five times greater than other customers.

In the digital realm, increasing loyalty comes down to removing the pain points and improving the overall shopping experience, says Slattery. “For example, we’ve learned that consumers have an easier time finding a brand, say Diet Coke, than finding a specific product, such as a 12-ounce eight-pack of Diet Coke plastic bot-tles. That is why we’re working with our retail partners to improve the navigation and search experience.”

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”Julia Millot, Senior Research Analyst, 1010data

Even the most sophisticated data-centric retailers do not know what led shoppers to visit a particular store.

DIGITAL SHOPPING: FROM CLICKSTREAM DATA TO KEYWORD SEARCHMarketers have an opportunity to learn more about the interim purchase steps on-line than in a physical store, thanks to all of the available online data. Clickstream data, for example, can supplement online sales with browsing histories, allowing consumer brand marketers to know who is visiting e-commerce sites where their products are being sold, which products they are looking for, how they browse or comparison shop, and so on.

“Even the most sophisticated data-centric retailers do not know what led shoppers to visit a particular store or which items those shoppers picked up or put back on the shelf before making their purchases,” says Julia Millot, Senior Research Analyst at 1010data. “This is where adding clickstream data can help illuminate the decision-making process. Where did the shopper origi-nate the search? Which other brands were considered prior to purchase and what search terms were used? What ads or product pages were clicked on? These are all insights that can be quantified and captured in the moment.”

Once marketers uncover patterns in these data sets, they can develop strate-gies to communicate with shoppers in more targeted and influential ways. “If I am Procter & Gamble and I see that a large number of Pampers shoppers are buying or considering Colgate over Crest online, I can start to think about how to increase loyalty across my brands in those two categories with more personalized commu-nications,” notes Millot.

Keyword search in particular is playing an important role in driving con-sumers’ online purchases. Per 1010data, 60% of online purchases begin with search. Thus, marketers are constantly looking to improve their SEO bidding practices and ensure that their brands end up as high as possible on search returns, especially on Amazon.com.

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Where the Journey BeginsPercent of Purchases by Referring Site

15%16%

13% 13% 13%

12%

6% 6% 6% 6%

5% 5%4% 4% 4%4%

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YoutubeYahooFacebookGmailDirect to Purchase Site

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Direct to purchase site means that if a consumer purchased on Amazon.com, then they opened their browser and went straight to Amazon.com. If they were on Facebook or Gmail, there's a chance they clicked on an ad that directed them on their path to purchase, but this data does not directly attribute that. The consumer also could have just been checking email and then decided to begin a shopping journey.

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“Keyword search optimization runs counter to how you normally think as a marketer, which is to condense a compelling idea into as few words as possible,” notes Grzymajlo. To maximize results, she says that product detail pages should contain content and language that captures as many common search terms as possible. In addition, marketers will want to stay out ahead of popular consumer trends. In pet food, for example, a search term like “freeze-dried raw” might not be top of mind with every shopper, says Gryzmajlo. “But if it is consistent with your brand identity, you’ll want to include it before somebody else takes it away from you.”

These tactics have a proven ability to increase sales and market share. A lead-ing protein powder manufacturer recently regained its number one category status online when it switched its product descriptions on Amazon.com from “nutritional shake” to “plant based protein powder,” as the latter term was far more common in searches. Plant protein powder is a $170 million per-month cat-egory, so this marketer realized $13.6 million in incremental sales in one month, per 1010data. “Consumers are getting more personalized and specific with their keyword searches, and marketers are now realizing that the more detail they can include in the product names or descriptions, the less likely they will be missed in search results,” says Millot.

FROM DISCOVER TO PURCHASE: BREAKING DOWN THE DECISION JOURNEYOn the following pages, we present an analysis of the consumer decision jour-ney in four major stages: Discover; Consider; Evaluate; and Purchase. Each of these sections contains examples from 1010data’s research conducted over a 12-month period ending in June 2018 in the whey protein powder, dry dog food and cookie categories. Charts and graphics illustrate key takeaways throughout the discussion.

Growing Reliance on On-Site SearchPercent of Sales Starting with Search

27% 60% 4% 10%

38% 45% 8% 10%

33% 55% 4% 9%

Cookies

Dry Dog Food

Whey Protein Powder

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Non-search means that those purchases were found without any search (on or off-site), which likely means they went directly to a product page or clicked through a site to get to what they were looking for. Off-site search refers to searches made on search engines, like Google or Bing. On-site search refers to searches made with the search engine on a particular retailer's website, like Amazon or Walmart. Both means that they searched off-site and then again on-site.

STAGE ONE: DISCOVEREvery digital marketing manager wants to know: What factors trigger a con-sumer to begin their buying journey online? In today’s environment, consum-ers are constantly exposed to various stimuli that can initiate a buying deci-sion. Whether it comes from social media or an email promotion, there’s a moment when the consumer decides that they need or want to buy something. Getting the right exposure by channel is critical during this awareness phase: Nearly 70% of brand choices are made at the beginning stage of the consumer decision journey, per McKinsey’s research.

In this early awareness stage, data with regard to referred sites — the last site the consumer visited before beginning the path to purchase — is critical. About 88% of online purchases begin on a site other than the one the consumer actu-ally purchases from, per 1010data. These consumers are coming from search engines, social media pages, email accounts and possibly even competitor’s sites as they go through their decision journey. Knowing the distribution of referring sources to a brand’s site or product page can help the marketer spend advertis-ing dollars more efficiently and optimize strategies to increase conversions.

For example, in Fig. 1, on page 5, we see that in the dry dog food category, consumers are more likely to begin their journey on Yahoo! (either while on email or having clicked on an ad), while consumers in the whey protein and cookies categories spend more time in the discovery stage on Facebook and YouTube. “A few percentage points difference in this stage could mean the dif-ference of millions of clicks,” notes Mantis.

STAGE TWO: CONSIDERWhen shopping in-store, consumers roam through aisles to explore and ul-timately select their items. Online, it’s all about search. Whether originat-ing from a search engine or through an on-site search bar, this consideration process is a critical first step toward converting a new or returning customer. “Click-through rates (CTRs) will indicate if your marketing efforts are per-forming well, but conversions by search term will help you justify your SEO spend,” notes Frank Riva, Vice President of Demand Generation and Growth Marketing at 1010data.

In Fig. 2, at left, we see that the majority of purchases in the whey protein pow-der, dry dog food and cookies categories originated from or included some type of search, although the percentages varied widely in those categories, as did the proportion of on-site/off-site searches. In general, 87% of purchases that begin with search do so directly on-site — i.e., within a particular retailer’s website, such as Walmart.com or Amazon.com. This suggests a deepening loyalty to those retailers (and perhaps less of a reliance on general search engines), which is con-sistent with the effort that online retailers including Walmart and Target have made in recent months to improve their websites’ design, functionality and over-all customer experience.

In addition, more than 80% of online CPG purchases that originated in search used generic category terms such as dog food, coffee or toothpaste, which means more than a fifth of the pie was composed of more detailed and specific search terms. Getting out ahead of consumer trends via search data can help a business anticipate those trends and respond with marketing accordingly. By now, most marketers know that “fidget spinner” followed by “Nintendo switch” were two of the most popular consumer products of 2017, but the daily search data showed just how quickly these items gained in popularity in real-time.

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Organizations need to integrate all these systems to get the singular view of the consumer.

Frank Riva, Vice President of Demand Generation and Growth Marketing, 1010data

STAGE THREE: EVALUATEKnowing which brands or retailers pose the biggest competitive threat can help a marketer win back customers during their next purchase cycle. Overall, nearly one-third of all consumers consider other brands in any given category, and 22% consider other merchants during their online buying journey. As an example, brand loyalty (as measured by consideration of other brands) in dry dog food and cookies is generally higher than in the whey protein powder cate-gory (see Fig. 3). Even so, a well-known cookies manufacturer like Nabisco has a relatively high rate of competitive consideration (18%). “By breaking down that number to see exactly where the competition is coming from, Nabisco can develop more targeted communications and get its numbers more in line with its rivals in the category,” notes Millot.

Strong product content is critical in this stage. The ability to switch seam-lessly between different product pages or even merchants without physically moving empowers consumers to be very careful in their consideration and evaluation of the infinite number of items presented to them online. In fact, 98% of shoppers have been dissuaded from completing a purchase because of incomplete or incorrect content. Consumers will use the product details as their benchmarks for evaluation before making a final decision.

It is also critical to carry the flavors, sizes and styles of products that con-sumers prefer. Utilizing historical purchase behavior, brands and retailers can determine which trends are emerging or still resonating amongst con-sumers. In 2017, per 1010data, lime was the most popular sparkling water flavor purchased online; more than 55% of salty snacks were purchased in a pack of 12 or more; and 25 of the top 100 selling shampoos online were in 33.8 oz. bottles.

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Whey Protein Powder Dry Dog Food Cookies

MusclePharm 27% Rachael Ray Nutrish 15% Nabisco 18%

MuscleTech 26% Taste of the Wild 13% Grandma’s 18%

EAS 22% Purina ONE 11% Archway 15%

Body Fortress 22% Wellness 10% Keebler 14%

BSN Sports 17% Nutro 10% Walker’s Shortbread 13%

Dymatize 17% Blue Buffalo 9% Chips Ahoy 13%

Isopure 16% Pro Plan 9% Newtons 10%

Now Foods 16% Natural Balance 8% Pepperidge Farm 10%

CytoSport 12% Hill’s Science Diet 7% Oreo 8%

Optimum Nutrition 12% Royal Canin 6% Biscoff 5%

A Full Competitive ViewPercent of Purchase Sessions that Compared Brands

Percent of purchases for individual brands in which the consumer looked at the product pages for other brands. The lower the percentage, the more "loyalty" for the brand (i.e., consumers did not consider other options). A purchase session is considered to be three days or less for one consumer.

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VALUING DATA: WHAT’S IT WORTH?A guide to third-party data classification and strategies for

outsourcing in a saturated data marketplace

y now, most marketers recognize that they do not always have ownership over all the data they need and must look outside the organization to fill in the gaps. But when it comes to putting a

price tag on all of that available data and deciding when, where and how much to invest in third-party data col-lection services, marketers often find themselves asking: “What is this data worth to me?”

The answer depends on the specific use case and situation, says Steve Albert, Chief Operating Officer at 1010data. “A marketer’s strategic approach to outsourc-ing data will differ if it is making pricing optimization de-cisions in a fragmented, primarily online category where it is the eighth-ranked player, versus if it is trying to de-termine a promotional strategy in a highly concentrated category in which it is the market leader.”

CPG marketers face a unique set of challenges. Unlike an online retailer or, say, an electronics firm that sells di-rect to consumers, they do not have access to internal online sales data that can show how they are performing relative to the category. “The average CPG company has many blind spots in e-commerce. There’s a lot of white space,” says Andy Mantis, SVP of 1010reveal, the com-pany’s data insights business. “For example, a household products brand might be an overall category leader in the market but it does not know if 50% of its customers are abandoning for upstart brands online because there are so many high quality better-priced options.”

Marketers must also consider their approach to data analysis in the context of overall brand strategy, adds Albert. “For highly strategic approaches involving ma-chine learning, one would prioritize the amount of his-torical data, coverage, depth and accuracy. Other ap-proaches are more judgment based, in which case the marketer may rely more on intuition into where the big-gest blind spots are that need to be filled.”

As with any investment decision, marketers need to quantify the potential business value of overlaying inter-nal data with third-party sources, and compare costs to those of a given brand initiative (e.g., introducing a new line extension) that will be driven by the data. “Often times, we see the justification for new data is made by various groups — marketing, merchandising and consum-er insights — coming together to jointly fund the initiative, which will support a number of decision-processes.”

Below is a guide to assist marketers in the process of valuing all the different classes of third-party online data.

• Clickstream data: Data that captures an anonymized user’s URLs across retail browsing activity. The value of clickstream data lies in a brand manufacturer’s ability to track a consumer’s online shopping journey from start to finish, including search terms employed, sites/ads clicked on, other brands considered, and so on.

• Credit/debit card transaction data: These data points are of particular value to a retailer that wants to know more about its omnichannel share: the breakdown of sales in-store and online; how those figures compare to the broader market; how consumers are cross shopping between stores; whether there is a leakage of customers from in-store to online; whether a specific promotion caused one retailer to lose customers to a certain competitor; etc.

• E-mail receipts: Like credit & debit card data, email receipts expose lifetime customer value metrics to retailers. Since email receipts include item-level detail, this further assists retailers in adjusting their merchandising strategy by comparing to products trending in the market. This data set is highly valuable to brands that want to optimize trade spend allocation and understand their position in the market.

• Social sentiment data: This is the large and exponentially growing category of unstructured data that lives throughout the Internet. Social sentiment data helps a marketer understand consumer sentiment and predict future trends. There are many independent companies that provide access to unstructured text and images across social, online public and enterprise-held data platforms, offering solutions that analyze audiences, track brand perception and campaign performance.

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Steve Albert, Chief Operating Officer, 1010data

For highly strategic approaches involving machine learning, prioritize the amount of historical data, coverage, depth and accuracy.

STAGE FOUR: PURCHASEJust how difficult is it to win buyers online? The average online conversion rate is a mere 3%. Using aggregate online data sources (e.g., clickstream, credit cards, email receipts, etc.), however, a brand may determine its conversion rate at individual on-line retailers as compared with the rest of the category or broader digital market. Those insights can help determine investment strategy across dozens of e-com-merce sites. For example, a salty snacks brand considering channel investments for the Staples and Sam’s Club websites saw that Staples’ had a high conversion rate of 10.2% in their category, but that Sam’s Club generated four times more salty snack sales online. Combining the sales volumes and conversion rates led the salty snacks brand to an understanding that they could generate six times more sales through Sam’s Club than Staples, ultimately optimizing their strategy and maximizing ROI.

As consumer preferences change, the market has responded with new avenues for online shopping, including marketplaces, direct-to-consumer sites and sub-scription options. Amazon’s Subscribe-and-Save option saw a dramatic 130% in-crease in sales through that channel in 2017, making it one of the fastest growing retailer segments for consumer goods companies. DTC’s share of online sales, meanwhile, has declined in both beauty and athletic shoes from 2016 to 2017.

WHAT’S NEXT: CONSOLIDATION AND INCREASED PERSONALIZATIONAsk any marketer right now about their holiday wish list, and chances are the words data, personalization and customer experience will be included at or near the top. Providing the optimal consumer experience is probably the big-

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Tracking Sales & Conversion RatesPercent of Units Sold in Category by Retailer

Whey Protein Powder Dry Dog Food Cookies

amazon.com – direct 44% chewy.com 44% walmart.com – grocery 30%

amazon.com – subscription

19% amazon.com – subscription

20% amazon.com – market 12%

amazon.com – market 17% amazon.com – direct 17% amazon.com – direct 11%

bodybuilding.com 11% petsmart.com 4% shipt.com 8%

vitaminshoppe.com 3% petco.com 4% peapod.com 7%

gnc.com 3% walmart.com – grocery 3% walmart.com – 1P + 3P 7%

vitacost.com 1% petflow.com 2% amazon.com – subscription

6%

walmart.com – 1P + 3P 1% walmart.com – 1P + 3P 2% shoprite.com 5%

costco.com 1% amazon.com - market 2% instacart.com 4%

walmart.com – grocery 1% instacart.com 1% freshdirect.com 2%

gest priority — and, in many cases, the biggest challenge. Rapidly changing con-sumer needs and a steady influx of new digital avenues increase the difficulty of staying ahead of shifting trends. But if marketers can manage to harness the seemingly limitless supply of unstructured digital data, a deeper understanding of the consumer decision journey and the relative opportunities within critical decision points rests at their fingertips.

“At the end of the day, success will come down to the consolidation of data,” says Riva. “For now, data in most companies resides in different business units and disparate systems, and is being overseen by different functions within the marketing department.

“Organizations need to keep working to integrate all these systems to get the singular view of the consumer that they need for optimal success, not only in e-commerce but in all channels, using all platforms and touchpoints at their disposal.”

For retailers, there are many opportunities to impact consumer shopper be-havior online, particularly in grocery. “If consumers are ordering groceries on-line and they only buy some produce and canned goods, there isn’t anything prompting them to consider adding a dairy or frozen food product,” says Millot. “Retailers don’t need to do this in-store, since shoppers are conditioned to a store layout where walking down an aisle can trigger a need or desire to buy something spontaneously. Online, they have the opportunity to remind or trigger the shop-per to fill out their baskets.”

For all marketers, e-commerce data does not exist in a vacuum. In fact, it is often a better indicator of overall consumer trends than what is happening in stores and can actually impact the in-store shopping experience by determin-ing supply and demand, argues Riva. “Online purchase behavior data is help-ing brands and retailers anticipate and respond to the next wave of competi-tion earlier than before,” he says. “Brands that established manufacturers have never heard of can become tomorrow’s category leaders but can also become great acquisition opportunities.”

For all these reasons, companies like 1010data will keep pounding the drum on the need to bridge data’s divide. n

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ABOUT THE AUTHORMichael Applebaum is a freelance writer and editor with a journalism back-ground who specializes in developing various forms of custom content. He works directly with senior agency and business executives on thought leader-ship programs to publish articles in the form of LinkedIn posts, digital media blogs, magazine features, white papers and special reports. He has written extensively on topics including technology, emerging media, digital adver-tising, retail, e-commerce and global economic trends. Michael has covered marketing for nearly 20 years. He was senior features editor for Brandweek from 2000 to 2006. His work has been regularly featured in AdAge, Adweek, Huffington Post, Forbes, Fortune, MediaPost and CPG Matters and Shopper Marketing magazine. He is based in Chicago.

1010data transforms Big Data into smart insights to create the high-definition enterprise that can anticipate and respond to change. Our modern cloud-based analytical intelligence and alternative data solutions enable over 850 clients to achieve improved business outcomes quicker, with less risk. The world’s foremost companies, including Rite Aid, Dollar General, Procter & Gamble, Coca Cola, GSK, 3M, Bank of America and JP Morgan, consider 1010data the partner of choice for mastering customer touchpoints, optimizing product portfolio health and digital-ly renovating operations. We’ve been recognized as a Challenger in the Gartner Magic Quadrant for Data Analytics Solutions, named a Leader in the Forrester Wave for Cloud Business Intelligence Platforms and honored as a Big Data Analytics Player by Information Week. 1010data is delivering on the promise of Big Data, and we’re just getting started.

The Path to Purchase Institute is a global association serving the needs of brands, retailers, agencies and the entire ecosystem of solution providers along the path to purchase. The Institute focuses on the forward-looking challenges and issues confronting our members and the shopper marketing industry at large. We facilitate industry interaction and foster best practices and a deeper under-standing of all marketing efforts and touchpoints that influence and culminate in purchase decisions in-store, online or anywhere along the path to purchase.

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